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Quantum algorithms have demonstrated extraordinary potential across numerous fields, offering significant advantages in solving practical problems. Power Quality Disturbances (PQDs) have always been a critical factor affecting the stability and safety of electrical power systems, and accurately detecting and identifying PQDs is crucial for ensuring reliable system operation. This paper explores the application of quantum algorithms in the field of power quality and proposes a novel method using Quantum Support Vector Machines (QSVM) to detect and identify PQDs, which marks the first application of QSVM in PQD analysis. The QSVM model employed involves three main stages: quantum feature mapping, quantum kernel computation, and model training. Quantum feature mapping uses quantum circuits to map classical data into a high-dimensional Hilbert space, enhancing feature separability. Quantum kernel computation calculates the inner products between features for model training. Rigorous theoretical and experimental analyses validate our approach. This method achieves a time complexity of O (N 2 log (N)) , superior to classical SVM algorithms. Simulation results show high accuracy in PQDs detection, achieving a 100% detection rate and a 96.25% accuracy rate in single PQD identification. Experimental outcomes demonstrate robustness, maintaining over 87% accuracy even with increased noise levels, confirming its effectiveness in PQDs detection and identification. [ABSTRACT FROM AUTHOR]

The rapid development of electric vehicles (EVs) has created more possibilities for their flexible participation in electric power dispatching. Considering the clustering and fast mobility of EVs coinciding with real-time market requirements for responsive demands, a bidding strategy is proposed in this paper to assist EV aggregators with submitting reasonable quotations for the real-time market. Based on Bayesian updating, the strategy in this paper considers relevant factors such as aggregator cost and expected return. First, a quotation strategy in electricity spot market is proposed for EV aggregators. Second, the applicable scope of the strategy is given under different scenarios. Then, the objective function of learning is proposed, and the specific process of Bayesian updating is demonstrated. Finally, a case study of the aggregator quotation strategy based on Bayesian updating is simulated to verify the effectiveness and feasibility of the proposed strategy, which helps improve the bidding success rate of EVs and peak-to-valley balance of the grid. [ABSTRACT FROM AUTHOR]

In this paper, a double-pole double-throw analog switch with n-channel architecture driven by a charge pump is described. The architecture proposed in this paper not only can reduce the on-resistance of the complementary metal oxide semiconductor (CMOS) switch, but also can realize a stable on-resistance within the full swing range of the input signal. This analog switch has the characteristics of high-speed, low-voltage, and high linearity, which is suitable for high-speed USB (Universal Serial Bus) 2.0 applications and meets low-speed and full-speed USB requirements. The test chip using a 0.25 μm BCD (bipolar–CMOS–DMOS) process confirms the characteristics of the switch. It uses + 2.8 to + 5.5 V single power supply, and the normal operating temperature range is − 40 to + 85 °C. This switch has an over-voltage protection function, which can prevent damage to the switch from the high input voltage. Besides, the switch port can realize dual-direction transmission. The analog switch designed in this paper solves some problems of traditional analog switches, such as large on-resistance, large supply current, and large parasitic capacitance. The on-resistance of the analog switch architecture in this paper is 5 Ω and the on-resistance flatness is 0.1 Ω. The supply current is as low as 0.87 μA while the whole chip area is 0.65 mm2. [ABSTRACT FROM AUTHOR]

Offshore wind farms (OWFs) play a crucial role in producing renewable energy in modern electrical power systems. However, to ensure that these facilities operate smoothly, they require robust control systems. As a result, this paper employed the newly developed Walrus Optimization algorithm (WaOA) to optimize the design parameters of fractional-order proportional-integral-derivative (FOPID) controllers in the power electronic interface circuits of the studied wind energy conversion system (WECS). In contrast to conventional optimization techniques like GA and PSO, the suggested approach proves more effective. The paper validates the WaOA application in optimizing FOPID controllers within a WECS comprising two, onshore and offshore, VSC stations at the two ends of an HVDC transmission system connecting OWFs to the mainland. The study shows that the WaOA outperforms GA and PSO, improving system stability and enabling quick recovery after disturbances. The study carried out using MATLAB/Simulink highlights the significance of newly recently introduced optimization techniques to ensure efficient and reliable operation of offshore wind energy systems, thereby expediting the transition to sustainable energy sources. [ABSTRACT FROM AUTHOR]

In the ship's electrical power system, the largest percentage of a load powered by an induction machine (IM) can be represented through the fan load characteristics. Likewise, it is well known that, from the point of view of the current load, the "most problematic" way of starting the induction machine is the direct start. This paper deals with a novel analytical modeling of the IM direct start-up speed–time curve under fan load. The derived analytical expressions have been used for modeling the start of induction machines of different powers and voltage levels. Also, the obtained results have been compared with the corresponding results provided by using the realized MATLAB/Simulink model of the induction machine coupled with fan load. Moreover, the results obtained have been compared with the methods presented in the literature as regards the modeling of start-up characteristics. The experimental validation of the proposed analytical expressions for modeling the direct start of IM driving fan load has also been carried out on a 300 W machine in a laboratory environment. Both the simulations and experimental verification have demonstrated an exceptional accuracy of the derived analytical expressions. The paper also provides the implemented MATLAB code for determining the speed–time curve of IM during direct start under fan-type load. [ABSTRACT FROM AUTHOR]

The state of New York admitted 143 million metric tons of carbon emissions from fossil fuels in 2020, prompting the ambitious goal set by the CLCPA to achieve carbon neutrality. The paper focused on analyzing and predicting carbon emissions using four different machine-learning algorithms. It examined emissions from fossil fuel combustion from 1990 to 2020 and validated four different algorithms to choose the most effective one for predicting emissions from 2020 to 2050. The analysis covered various economic sectors including transportation, residential, commercial, industrial, and electric power. By analyzing policies, the paper forecasted emissions for 2030 and 2050, leading to the identification of different pathways to reach carbon neutrality. The research concluded that in order to achieve neutrality, radical measures must be taken by the state of New York. Additionally, the paper compared the most recent data for 2021 with the forecasts, showing that significant measures need to be implemented to achieve the goal of carbon neutrality. Despite some studies assuming a trend of decreased emissions, the research revealed different results. The paper presents three pathways, two of which follow the ambitious plan to reach carbon neutrality. As a result, the emission amount by 2050 for the different pathways was projected to be 31.1, 22.4, and 111.95 of MMt CO2 e, showcasing the need for urgent action to combat climate change. [ABSTRACT FROM AUTHOR]

This paper is an attempt to provide a dual-source inverter, an intelligent inverter topology that links two isolated DC sources to a single three-phase output through single-stage conversion. The converter is designed to be utilized in hybrid photovoltaic fuel cell systems, among other renewable energy applications. The proposed dual-source inverter employs a single DC-AC converter, as opposed to conventional dual-source hybrid inverters which make use of several input DC-DC modules to obtain the voltage formed across the inverter's input DC-link. In the proposed topology, the semiconductor count is low, which leads to improved efficiency, cost, complexity, and reliability. The proposed topology makes use of two impedance networks connected by transformers, diodes, and capacitors. The regulation of the electrical power generated by primary sources and the independence of the converter on key factors like voltage and frequency are essential parameters in multi-input converters. This feature becomes highly prominent when the control algorithm is implemented by conventional processors. Viewed from this perspective, the control method described in this paper is worthy of consideration. The research work describes a 220-W/50 Hz prototype that employs Simple Boost-SPWM. Experimental results verify the analyses and corroborate the satisfactory performance of the suggested converter. [ABSTRACT FROM AUTHOR]

Most of countries around the world tends to increases the penetration of renewable energies generation in electrical power networks. This led to the emergence of many challenges in these systems, such as congestion of lines, voltage instability, etc. The most important of these problems is the spillage of renewable energies in order to maintain the stability of the power system. However, by using the traditional methods to mitigate the spillage, the stability of the power system may be deteriorated leading to a vulnerable power system against disturbances. This paper proposes a bilevel multi-objective Musical Chairs optimization algorithm for optimal allocation of multi-type flexible AC transmission system (FACTS) devices. The main target of the upper-level is to reduce the wind power spillage with minimize the investment cost of FACTS devices and load shedding, while maximize the voltage stability. Moreover, under different operating scenarios, the lower-level problem captured the market clearing with maintain the system constraints for maximize the social welfare. This leads to a robust and economical operating point where included enough levels of voltage security. The technique proposed in this paper is tested on the IEEE 24-bus modified reliability test system. The results show that the applicability of the proposed algorithm in aiding power system improvement planning for minimizing wind power spillage to integrate wind energy with maximizing the social welfare and improving the loadability and the voltage stability. [ABSTRACT FROM AUTHOR]

Power transformers are a key component of electrical networks, and they are both expensive and difficult to upgrade in a live network. Many utilities monitor the condition of the components that make up a power transformer and use this information to minimize the outage and extend the service life. Routine and diagnostic tests are currently used for condition monitoring and appraising the ageing and defects of the core, windings, bushings and tap changers of power transformers. To accurately assess the remaining life and failure probability, methods have been developed to correlate results from different routine and diagnostic tests. This paper reviews established tests such as dissolved gas analysis, oil characteristic tests, dielectric response, frequency response analysis, partial discharge, infrared thermograph test, turns ratio, power factor, transformer contact resistance, and insulation resistance measurements. It also considers the methods widely used for health index, lifetime estimation, and probability of failure. The authors also highlight the strengths and limitations of currently available methods. This paper summarizes a wide range of techniques drawn from industry and academic sources and contrasts them in a unified frame work. [ABSTRACT FROM AUTHOR]

Recent years have witnessed the remarkable progress in wireless communication systems due to the escalating demand for higher data rates, improved reliability, and increased energy efficiency. In this regard, Non-Orthogonal Multiple Access (NOMA) has emerged as a promising technology, enhancing spectral efficiency and accommodating multiple users concurrently within the same time and frequency resources. Simultaneously, the energy harvesting has surfaced as a sustainable solution, converting ambient environmental energy into usable electrical power for operating communication nodes. This paper proposes a cooperative NOMA transmission scheme integrating energy harvesting and utilizing Least Squares (LS) channel estimation for precise Channel State Information (CSI) acquisition. The objective is to establish an optimal communication path from source to destination. Relay selection methods: Optimal Relay Selection (ORS) and Max-Min Relay Selection (MMRS), are compared, focusing on their impact on the system performance. The analysis considers the influence of the number of relays and power allocation factor on the system, with a specific emphasis on the outage probability expressions. Comparative analysis between the cooperative-NOMA and the traditional cooperative relaying without NOMA reveals the superior performance of the cooperative-NOMA. Additionally, the ORS scheme outperforms MMRS in terms of the outage performance. [ABSTRACT FROM AUTHOR]

A Lead-Cooled Fast Reactor (LFR) is one of the six advanced fourth-generation reactors that many countries have been interested in designing, constructing, or develop them in the world. ALFRED reactor design investigated in this paper has 125 (MW) electric power and is being cooled by lead. The main purpose of the ALFRED project is to design and construct a reactor with high safety performance and reliability in all operation modes. In the present study, Monte Carlo codes MCNPX and SuperMC are used to calculate the neutronic parameters of the ALFRED reactor core including effective multiplication factor, kinetic parameters, neutron flux, and power distribution based on the latest design data. According to the results, the insertion of the control rods into the core can move the maximum flux height of about 40% to 50% to the end. Also, comparing codes' results show an appropriate consistency. [ABSTRACT FROM AUTHOR]

The detection of defects on small cotter pins that are installed in electric power fittings is an essential part of the inspection task of overhead lines using Unmanned Aerial Vehicles (UAV). It is challenging to detect small defects from a large number of UAV images. In this paper, an efficient and high-performance defect detection model called DDNet is proposed to recognize defects from images of unmanned aerial vehicles. The attention mechanism was adopted in the improved detection model in order to enhance the representation learning of the image. Inspired by the human visual system, the RFB module is added to the FPN module, increasing the receptive field of the entire detection network, which is conducive to the detection of small objects. Then a dataset of cotter pins for model training and testing was introduced. The study demonstrates that the proposed DDNet increases the average precision from 82.0 to 90.1% and reduces the miss rate of defect detection from 14.5 to 7.4% in our dataset compared to the baseline RetinaNet model. We also compared existing frameworks for object detection and discussed other common ways to improve precision. The results showed that our optimized model in this paper improved detection performance, which subsequently proved the practicability and effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

In electrical power systems, FACTS devices effectively control power flow and change bus voltages, leading to lower system losses and excellent system stability. The article discusses the research from the last decade that evaluated various methods for placing FACTS devices using the meta-heuristic approach to address the positioning of FACTS devices to maintain proper bus voltages and control line flow and improve the overall system efficiency. The need for more efficient electricity systems management has given rise to innovative technologies in power generation and transmission. The combined cycle power station is a good example of a new development in power generation and flexible AC transmission systems, generally known as FACTS, are controllers that improve transmission systems. Worldwide transmission systems are undergoing continuous changes and restructuring. They are becoming more heavily loaded and are being operated in ways not originally envisioned. Transmission systems must be flexible to react to more diverse generation and load patterns. In addition, the economical utilization of transmission system assets is of vital importance to enable utilities in industrialized countries to remain competitive and to survive. In developing countries, the optimized use of transmission systems investments is also important to support industry, create employment and utilize efficiently scarce economic resources. FACTS controller is a technology that responds to these needs. It significantly alters the way transmission systems are developed and controlled together with improvements in asset utilization, system flexibility and system performance. Several models and techniques suggest that devices can be placed in a particular location with different parameter settings. Finally, the optimization problem improved system performance by decreasing power loss, improving the voltage profile and power angle at each bus, raising the L-index, and minimizing generating costs. FACTS devices can increase the transmission line's capacity for transferring power by increasing the voltage at its terminals at both ends and reducing line reactance. The FACTS controller must be installed in the distribution and transmission lines to maximize the power flow. Various techniques are used for the best placement of FACTS controllers, including analytical methods, arithmetic programming approaches, meta-heuristic optimization approaches, and hybrid approaches—this paper analyses numerous analytical and meta-heuristic optimization techniques to place FACTS controllers in the most advantageous locations. The fundamental problems in intelligent power systems, such as improving stability, power quality, and managing congestion, are discussed in this study, along with several applications of FACTS devices. The cutting-edge power systems of today provide users with constant, high-quality power through smart grids and smart meters. [ABSTRACT FROM AUTHOR]

The application of a standalone photovoltaic (PV) system for water pumping has increased nowadays in remote areas of developing countries due to proven economic feasibility compared to other traditional alternatives. Pump–motor set manufacturers always give the pump characteristic at the motor's nominal speed. The traditional selection process of pumps depends simply on selecting a pump with the highest peak efficiency that can satisfy the desired duty point with its peak efficiency occurring at that duty point. However, this simple selection process could lead to selecting a pump that is not the best selection from among a given set of candidate pumps for the targeted service. In this paper, this fact is revealed by comparing two pumps each having the same peak efficiency and each of them can operate at the desired duty point with one critical difference between the two pumps. One of the two pumps has its peak efficiency occurring at the right of the duty point and the other has its peak efficiency occurring at the left of the desired duty point. The methodology of this research is based on calculating the daily efficiency of each pump by calculating the hydraulic power produced with the electrical power of the solar system. The efficiency calculation has been calculated over two working days, one with low radiation (3 kW/m2/day) and the other with high radiation (7.3 kW/m2/day). The search for the all-day efficiency for low radiation levels revealed that the pump with left-shifted peak efficiency gives 42.5% while for high radiation level gives 40.3%. In two cases the pump with left-shifted peak efficiency constitutes the best choice. Highlights: We propose a new method to select the best PV pumping system. The proposed method uses a simplified method to compare between two completely identical PV pumping systems except for the use of two different centrifugal pumps. This method aims at selecting the proper centrifugal pump according to maximum all-day efficiency. The proposed method was tested under the different solar radiation levels. [ABSTRACT FROM AUTHOR]

Background: The transition towards renewable energy sources has become an imperative step to mitigate climate change, reduce carbon emissions and improve energy security and economic prosperity in a sustainable manner. Maximizing the cost effectiveness of electric power generation is crucial to making renewable energy sources viable and attractive options for clean energy production. The strategic allocation of wind, hydro and solar power systems is essential to achieving this goal. This paper attempts to demonstrate how the cost effectiveness of electrical power system could be maximized through the integration of wind, solar and hydropower systems and comparison at different penetration levels of 0, 25, 50, 75 and 100% on cost effectiveness of electric power generation. The different generator technologies were designed based on their electrical output attributions. Results: The cost of electric generation for the integration of each generator at the various buses were calculated at different penetration level for fair comparison. The results indicate that the minimum money loss for the integration of solar power was $743.90 at bus 4 and at 50% penetration level, the minimum money loss for the integration of wind power was $999.00 at bus 4 and at 25% penetration level while the minimum amount loss for the integration of hydropower was $546.50 at bus 4 and at 75% penetration level. Conclusions: The magnitude to which the integration of the different generator affects the cost effectiveness of power production hinges on the type of generator, the penetration level and the location of the generator in the grid. [ABSTRACT FROM AUTHOR]

Electric charge service and management is an important part of electric power work. The effective recovery of the electric charge relates to the smooth development of daily work and continuous improvement of the operation and management of power supply enterprises. With the large-scale implementation of the card prepayment system, the problem of electricity customers defaulting on electricity charges has been solved to a large extent, but some large electricity users still fail to pay electricity charges on time. Therefore, under the current situation of power grid development, it is still necessary to strengthen the service and management of electricity charges to promote efficient recovery of electricity charges. Speech recognition technology has increasingly become the focus of research institutions at home and abroad. People are committed to enabling machines to understand human speech instructions and hope to control the machine through speech. The research and development of speech recognition will greatly facilitate people's lives shortly. The development of 5G technology and the proposal of 6G technology make the interconnection of all things not only a hope but also a reality. To realize the interconnection of all things, one of the key technical breakthroughs is the development of a new human–computer interaction sensing system. Under the guidance of relevant theories and methods, this paper systematically analyzes the user structure, electricity charge recovery management and service system, existing problems and causes in South China, and clarifies the necessity of design and application of electricity charge service system in South China power supply companies. The experimental data and empirical analysis results show that the optimized Bert fusion model can provide more digital support for the power supply companies in South China in terms of electricity charge recovery efficiency, management level system improvement, and electricity charge service. [ABSTRACT FROM AUTHOR]

Countries worldwide have pledged to phase out coal by 2030, giving rise to a fundamental reshuffling of the dynamics of energy demand and supply. Implementation of clean technologies to aid this transition necessitates space, whilst small islands face increasing land degradation issues. Furthermore, they are blessed with pristine remote environments that deserve enhanced protection in the face of the changing climate. In the current study, climatological, economic, legal, geotechnical, and environmental criteria are used to determine the most appropriate locations in Rodrigues for the constructions of utility-scale solar power plants to conserve native vegetation and protect vulnerable island ecosystems. Highly suitable sites identified include the regions of Terre Rouge and Pointe Coton. Both regions witness high levels of insolation (5.6 kWh/m2 day), are located near grid transmission and road networks, and have adequate terrain specifications with low slope angles which conveniently face the geographic North for maximizing solar energy yield. With an estimated annual electric generation power potential of 228.9 kWh/m2, the regions of Terre Rouge and Pointe Coton favour the construction of solar power plants. The methodological approach presented in this paper is expected to be valuable for other small islands in their commitments to optimize on solar technologies whilst protecting native fauna and flora. [ABSTRACT FROM AUTHOR]

This paper exhibits the coordinated control of 30 kVAr Distribution STATic synchronous COMpensator (DSTATCOM) with 125 kVAr Switchable Capacitor Banks for compensation of reactive power in a 750 kVA secondary radial distribution system. With the control of reactive power in a radial distribution system, the power factor can be improved near to unity. The selected radial distribution system mainly feeding power to vital loads of an Educational Institution. In this paper, the study of 750 kVA secondary radial distribution system is analyzed in terms of electrical power system of institute, power consumption pattern and tariff related issues. Some conclusions to improve the system performance in terms of power factor and reduction in tariff were drawn. The coordinated control of switchable capacitor bank and DSTATCOM performance depends on the calculation of the reference source currents that generates the gating pulses of the voltage source converter-based DSTATCOM. For this purpose, the control strategy adopted is Real and Reactive power (PQ) control, Synchronous Reference Frame theory, Back Propagation Control algorithm and Adaptive Linear (ADALINE) control is implemented in this system using MATLAB/SIMULINK software. Generation of the PWM pulses triggers the IGBT of the VSI-based DSTATCOM. This is achieved using DSP TMS 320 F 2812, a 32-bit processor that is programmed with CCS V3.3 and C2000 embedded code generation tool using MATLAB/Simulink, and the same is being executed with code composer studio V 6.0.1. The performance of the selected secondary radial distribution system is analyzed experimentally in a hardware prototype to evaluate the effect of DSTATCOM and switchable capacitor bank. [ABSTRACT FROM AUTHOR]

Cooling by micro-channel heat sink transfers excess heat flux in electrical devices and increases their functional capacity, reliability, and life span. In this paper, AlSi10Mg powders were employed to create four micro-channel heat sinks with cross-sections including square, rectangle, circle, and ellipse with an additive manufacturing method. To investigate the impact of micro-channel heat sink cross-sectional geometry on thermal resistance, Taguchi's L25 orthogonal array was utilized. Reynolds number and electric power were selected to be the input parameters. The experimental tests were conducted using an experimental setup and distilled water as the working fluid in the laminar flow regime. The results obtained from the experimental tests indicated that in the range of electric power from 4 to 12 W and Reynolds numbers of 50, 100, 150, 200, and 250, the micro-channel heat sink with a square cross-section exhibits the highest heat transfer performance. Finally, an analysis of variance was conducted to study the impact of the Reynolds number and electric power factors on thermal resistance. The findings revealed the significant effect of electric power on thermal resistance in micro-channel heat sinks compared to the Reynolds number in the laminar regime. Additionally, a comparison was made with other available results. [ABSTRACT FROM AUTHOR]

Copper-clad steel wire is widely used in electric power, railroads, automobiles, and other fields. However, how to balance production efficiency and wire quality is still a challenging task. In this paper, a continuous cladding composite casting method for copper-clad steel wire is proposed based on the hot-dip plating process, which adopts a removable graphite crucible and S-shaped wiring to control the thickness and eccentricity of the cladding metal, and at the same time adopts connecting the electrical resistance furnace with a water-cooled crystallizer to achieve rapid solidification, which in turn strengthens the mechanical properties of the copper-clad wire and thus realizes the rapid and continuous preparation of copper-clad steel wires with good quality. In this study, the optimum process parameters, including drawing speed and pure copper melt temperature, were provided to reveal the mechanism of metallurgical bonding at the solid–liquid composite interface. The circumferential uniformity, mechanical properties, and electrical conductivity of the prepared copper-clad steel wires were tested. The growth mechanism of the copper-coated structure and the mechanism of rapid solidification to strengthen the mechanical properties are described. The results have been plotted in graphs to describe the properties and characteristics of the materials. [ABSTRACT FROM AUTHOR]

To minimize total operating costs, emissions, and power losses, the optimum power generation and scheduling of renewable integrated hydro-thermal systems are one of the most significant objectives in short-term scheduling. The solution to these problems becomes more difficult with constraints and renewable uncertainties. The paper presents an improved cheetah optimizer (ICO) for solving the optimum wind-solar-hydro-thermal scheduling problem considering valve loading effects, ramp-rate limits, power loss, and prohibited operational zone constraints. The main objective is to optimize the total fuel cost and emissions for thermal power generators, where electric power can be fully harnessed from renewable generators. Different test systems are employed to evaluate the proposed ICO solution method's performance. The proposed ICO solution method is compared with other algorithms like grey wolf optimizer, and particle swarm optimizer, in terms of optimal fuel costs, emissions, convergence success rate, and computation time. The test systems are incorporated with wind farms, solar farm, hydropower generators, and thermal power generators scheduled for 24-h, 1-h subintervals. The simulation solutions of the renewable integrated system have been acquired by ICO, CO, GWO, and PSO. The total generation cost obtained by ICO is 0.0698%, and 0.1514% lower than the cost obtained by GWO, and PSO respectively. The total power loss was minimized by 1.8554% and 7.4002%. The total emissions can be reduced to 25% with increasing penetration of renewable energy sources. It is realized from the comparison that the proposed ICO method has the potential to provide better-quality solutions. [ABSTRACT FROM AUTHOR]

The electrical power system (EPS) has been heavily stressed due to high load demand. It operates close to the total capacity limits, resulting in voltage instability that can lead to voltage collapse. In this regard, incorporating flexible alternating current transmission system (FACTS) devices and renewable energy sources (RESs) to obtain the optimum values of the generator voltage, reactive compensation, and transformer tab in optimal reactive power dispatch (ORPD) is essential in increasing the reliability and safety of the system. ORPD involves discrete and continuous variables, which are nonlinear, noncontinuous, non-convex, and complex problems. The objective functions of ORPD are reduction in active power loss (Ploss), voltage deviation, and voltage profile enhancement. This paper presents a recent advancement of the ORPD problem, mathematical formulation of the objectives function, and a summary of various metaheuristic optimization methods (single and hybrid) used to solve the ORPD problems. The hybrid method combines two or more methods to improve the demerits of one method to obtain a quality solution to a problem. This review covered incorporating FACTS devices and RESs used in solving the ORPD problem to reduce the active Ploss and improve the voltage profile in the EPS. The benefits of FACTS devices and RESs are also discussed. Also, various metaheuristic algorithms (single, modified, and hybrid) employed to solve the ORPD problem were discussed. The future direction for researchers in this field was provided to give insight into the applicability and performance. Overall, this research explores different techniques used in solving ORPD problems from the optimization point of view to incorporating RESs and FACTS devices to obtain quality solutions. Some existing methods do not guarantee an optimum solution, but incorporating RESs and FACTS devices will help attain the best solution to the problem for better power system operation to improve system reliability and voltage profile. Based on the review journal, it can be concluded that hybrid techniques offer efficient quality solutions to the ORPD problem. [ABSTRACT FROM AUTHOR]

Most microelectromechanical systems (MEMS) devices require suspended structures with high metallic thickness, which is not possible with standard sputtering techniques. Electroplating-based UV LIGA is a cost-effective technique preferred for fabricating thick metallic structures. Gold is preferred as a structural material for MEMS devices such as RF switches, among other metals, due to its high conductivity and low reactivity. For electroplating, a constant current supply is applied between the cathode (electroplating wafers) and the anode (metallic mesh) dipped in gold electrolyte. The value of electric potential is determined by the constant current supply, which is determined by the plating area/current density. The standard DC current supply produces bone structures and non-uniform deposition across the wafer. The Helmholtz or electrical double layer plays a vital role in controlling the profile of the electroplated film. This paper addresses the issues of non-uniform deposition and bone structures with agitation, wafer rotation and bipolar pulsed power supply. [ABSTRACT FROM AUTHOR]

This paper presents the systematic design methodology of a 3.3 kW, level 2 battery charger with improved grid power factor for EV applications. The charging of the battery bank from the utility grid through bridgeless interleaved boost (BIB) converter and the proposed three-level modified series–parallel resonant converter is explained in detail. The proposed topology offers low voltage stress equal to half of the DC link voltage across the switches as three-level is implemented in the resonant stage. The transformer parasitics are taken into consideration and the design of resonant stage for frequency modulation is elaborated. One of the major concerns of the charging system is the grid power factor which is largely affected by power electronic switching operation. The detailed controller design procedure for power factor correction of BIB and DC link voltage regulation is elaborated in this paper. Simulation results obtained using PSIM software prove that the power factor is close to unity with less supply current total harmonic distortion as per IEC 61000-3-2 standard. The proposed resonant converter switches achieve zero voltage switching for above resonant frequency operation. [ABSTRACT FROM AUTHOR]

The application of computer vision continues to widen with advancement in technology. Imaging systems which provide necessary inputs to the computer-vision-based models can come in various ways. Such as X-ray images, Computed Tomography (CT) scan images, and Infrared (IR) images. This paper is a review of different application areas of infrared thermography (IRT) for monitoring the status of electrical power equipment. It summarizes in tabular form recent research and relevant works within the field of condition monitoring of power assets. A general review of the application of IRT in power devices was undertaken before a specific review of selected works based on IRT for important electrical power equipment with a tabular review of possible causes of hotspots using photovoltaic installation as a reference. Results of previous works were presented with highlights on performance metrics used and accuracies achieved. Emphasis where made on the future potential of IRT and some associated techniques. The work saw that heat production within systems during operation is an important characteristic that enables IRT to become applicable for monitoring diverse physical systems, most importantly power systems. The high cost of high-definition, and long-range IR cameras limits the wide adoption of the technology for its potential applications for monitoring power installations. The work recommends future research in the development of affordable IR imaging systems with advanced features for condition monitoring of physical systems such as power installations. [ABSTRACT FROM AUTHOR]

With the increasing of global awareness of the importance of reducing polluting emissions and maintaining a clean and healthy environment. So, the tendency to generate electric energy from new and renewable sources has become an urgent need to achieve this goal. In this paper an optimal economic cost analysis using hybrid renewable energy sources to generate the electricity needed for long-term evolution mobile phone systems was estimated. The proposed electric system accounts for the reduction of polluting emissions to the environment. The electrical profile of the optimal approaches or the hybrid technology and traditional methods which contain solar photovoltaic', batteries, wind turbines, diesel generator were estimated and provides the electrical power for a Long-Term Evolution mobile network (LTE) as the load at a remote located area. A real time optimal cost analysis of each proposed network is done based on the real load profile, wind speed and solar radiation was placid on from 6 October city in Egypt. Statistical analysis was performed by varying the systems through comparison to determine the optimal approaches based on the Hybrid Optimization Model for Electrical Renewables software (HOMER). [ABSTRACT FROM AUTHOR]

Industries using electrical power have a critical and pressing need for improved power quality (PQ). Several important problems have already been identified, such as voltage swell, sag, and harmonics. However, PQ fluctuation issues remain unresolved. A series of active power filters are used to shield delicate loads from PQ related problems. This paper present a low-complexity control technique for voltage compensation using a type of custom power device used with different inverter topologies called Dynamic Voltage Restorer (DVR). In this study, a three-phase Z-Source Inverter-based DVR is employed to reduce voltage disruption, including voltage fluctuation, sag, swell, and harmonics. Error-driven Proportional-Integral-Derivative (PID) controller provides higher PQ performance in terms of voltage augmentation, stabilization, and reduction in harmonic distortion in the distribution system. This strategy keeps the load voltage near or close to the nominal value and addresses many other voltage issues. The gain parameter of a PID controller is tuned using Harris Hawks Optimization (HHO) method. The proposed work is compared with traditional controllers as well as Genetic Algorithm-based PID controllers, and the distortion of total harmonics comparisons are also conducted to show the accuracy of the proposed Z-DVR. To demonstrate the effectiveness of the suggested methodology, it is implemented in MATLAB/Simulink R2020a tool and the results of the mitigated sag, swell fluctuation, and total harmonic distortion (THD) are studied. [ABSTRACT FROM AUTHOR]

Generator rotor angle oscillations can be caused by sudden changes in its mechanical power input or its electrical power output. When dampening or synchronizing torque is inadequate, rotor angle instability occurs, resulting in an increase in rotor angle, loss of synchronism, or oscillatory swings of the rotor angle with increasing amplitude. To this end, in this work, we offer a novel two-stage approach for predicting rotor angle stability following a large disturbance. The process begins with the creation of a database of dynamic simulation scenarios. This collection contains a wide set of stable and unstable rotor angle trajectories derived from different fault simulations. Then, the fuzzy c-means (FCM) clustering algorithm is utilized to put the sampled data of rotor angles with the highest degree of similarity in the same cluster. Angle sets generated by FCM are used to train the adaptive neuro-fuzzy inference system (ANFIS). Finally, the trained ANFIS is used to predict the future rotor angle stability situation of generators. In addition, a stability index is suggested in this article, which will assist ANFIS in more accurately predicting the stability condition. The efficiency of the proposed method is tested on the IEEE 39-bus system. The obtained results from simulations confirm that the proposed strategy can correctly predict the rotor angle instability or stability situation of generators in a few cycles after fault clearance. [ABSTRACT FROM AUTHOR]

The substitution of fossil fuels, especially coal, with renewable energy is a crucial step for the CO2 emissions reduction and the avoidance of Global Climate Change. The electric power generation industry is the first economic sector that will have to transition to renewable energy. However, wind and solar energy, the two most abundant renewable energy forms, are not dispatchable. The high penetration of these renewables in the energy market will create a demand–supply mismatch, which can only be alleviated with large-scale energy storage. This paper uses the case of Texas—a state that generates and consumes more electricity than several large, industrialized nations—to quantitatively examine the required infrastructure for the decarbonization of the electricity generation industry, while satisfying the current electric power demand in the State. Among the parameters that are examined are: the additional solar and wind capacity; the necessary energy storage infrastructure; the energy dissipation in the storage/regeneration process; and the effect of decarbonization on the cost of electricity and the welfare of the citizens. The computations show that the technology is available for the transition to a decarbonized electric power sector but requires significant investment in new wind and photovoltaic units as well as substantial energy storage. This would increase the electricity prices by a factor between 2.9 and 3.7 and, would have a disproportionate impact on the citizens in the lower income brackets. [ABSTRACT FROM AUTHOR]

Large solar power plants are installed in many countries, and they are connected to an electrical grid thereby providing an alternative to conventional energy sources. Photovoltaic cells are using solar energy directly and convert it into electrical power. To ensure there liable and safe operation of PV arrays, it is very essential to diagnose faults in PV arrays. Traditional fault detection devices are used for detecting line-to-line fault and open-circuit faults, if the magnitude of fault current defined as per international standards exceeds the threshold value. Due to several aspects like low irradiance condition, minimal fault mismatch, and active maximum power point trackers which minimizes the magnitude of fault current thereby resulting in fault identification becoming much more difficult. In case a fault in a PV array is not identified and the fault persists for a very long duration, it results in reliability issues and also it may lead to severe fire hazards. Hence, it is essential to identify the fault in a timely manner, and also localization is very much essential for sustainable power generation. This paper proposes new fault identification scheme for solar PV arrays connected in bridge and honeycomb configuration, and this method is capable to detect line-to-line fault and open-circuit faults with a minimum number of sensor requirement and also irrespective of the detection challenges. For real time, validation testing is carried out in a PV array, and the power gain due to the identification of line-to-line fault and line-to-ground fault is also investigated. [ABSTRACT FROM AUTHOR]

This paper examines the net environmental impact for the Fuel Cell Electric Vehicle, in special the Solid Oxide Fuel Cell Electric Vehicle (SOFCEV), by exploring how different fuels operate alongside the cell, through the analysis of its equivalent carbon dioxide emissions and energy-ecological efficiency. Thermodynamic analysis showed high theoretical efficiency for the SOFCEV with internal steam-reforming, mainly in the ideal temperature range indicated for equipment longevity. Ethanol and biomethane had minor environmental impact when compared to gasoline and glycerine. Biofuel-fuelled SOFCEV showed a thermodynamic performance like the obtained for gasoline. Also, biofuel-fuelled SOFCEV presented CO2e exhaust emissions capable to attend all future tailpipe emissions standards from the European Union and the United States. Glycerine had the lowest energy-ecological efficiency, while biomethane-fuelled SOFCEV has demonstrated to be the best energy and environmental scenario compared to the other analysed fuels. This paper might contribute to the reduction of climatic impacts related to the transport sector by showing that the SOFCEV achieve high energy-ecological efficiency when fuelled with biofuels. The use of biofuel-fuelled SOFCEV is considered a viable option that might enable decision making to favour the electromobility development. [ABSTRACT FROM AUTHOR]

An equivalent model for synchronous generators (SGs) in a wide-area power system is indispensable for lessening the computation burden of dynamic analysis. In this paper, we propose a discrete-time models (DTM) for SGs. DTM of SGs expedites the interconnection of equivalent models for describing SGs, and also improving the veracity of SGs in dynamic simulations. Firstly, the paper investigates the operational forms of SGs. Then, the paper expands the intrinsic relations among DTM parameters of SGs in the DTM with and without considering the bus angle. Besides, numerical contrast experiments are conducted based on the China Electric Power Research Institute-36 (CEPRI-36) system, and the veracity of DTM for SGs is verified by simulation results. Finally, the reason why the bus voltage phase angle variations are ignored of the DTM for SGs (or an equivalent aggregated generator) is shown in this paper. [ABSTRACT FROM AUTHOR]

Smart Grids are electrical grids that require a decentralised way of controlling electric power conditioning and thereby control the production and distribution of energy. Yet, the integration of Distributed Renewable Energy Sources (DRESs) in the Smart Grid introduces new challenges with regards to electrical grid balancing and storing of electrical energy, as well as additional monetary costs. Furthermore, the future smart grid also has to take over the provision of Ancillary Services (ASs). In this paper, a distributed ICT infrastructure to solve such challenges, specifically related to ASs in future Smart Grids, is described. The proposed infrastructure is developed on the basis of the Smart Grid Architecture Model (SGAM) framework, which is defined by the European Commission in Smart Grid Mandate M/490. A testbed that provides a flexible, secure, and low-cost version of this architecture, illustrating the separation of systems and responsibilities, and supporting both emulated DRESs and real hardware has been developed. The resulting system supports the integration of a variety of DRESs with a secure two-way communication channel between the monitoring and controlling components. It assists in the analysis of various inter-operabilities and in the verification of eventual system designs. To validate the system design, the mapping of the proposed architecture to the testbed is presented. Further work will help improve the architecture in two directions; first, by investigating specific-purpose use cases, instantiated using this more generic framework; and second, by investigating the effects a realistic number and variety of connected devices within different grid configurations has on the testbed infrastructure. [ABSTRACT FROM AUTHOR]

The main purpose of this paper is to develop an efficient machine learning model to estimate the electric power load. The developed machine learning model can be used by electric power utilities for proper operation and maintenance of grid and also to trade electricity effectively in energy market. This paper proposes a machine learning model using gated recurrent unit (GRU) and random forest (RF). GRU has been employed to predict the electric power load, whereas RF has been used to reduce the input dimensions of the model. GRU has been estimating the load with good accuracy. RF reduces the input dimensions of the GRU that leads lightweight GRU model. The main benefits of the lightweight GRU models are less computation time and memory space. However, lightweight GRU models will loss small amount of accuracy comparing to the original GRU model. GRU along with RF has been used for the first for short load forecasting. All the machine learning model's performance has been observed in stochastic environment. Impact of weekends on load forecasting also observed by considering the last 3-week load data. [ABSTRACT FROM AUTHOR]

Aiming at the energy efficient use and valorization of carbon dioxide in the framework of decarbonization studies and hydrogen research, a novel dielectric barrier discharge (DBD) reactor has been designed, constructed and developed. This test rig with water cooled electrodes is capable of a plasma power tunable in a wide range from 20W to 2 kW per unit. The reactor was designed to be ready for catalysts and membrane integration aiming at a broad range plasma conditions and processes, including low to moderate high pressures (0.05–2 bar). In this paper, preliminary studies on the highly endothermic dissociation of CO2, into O2 and CO, in a pure, inert, and noble gas mixture flow are presented. These initial experiments were performed in a geometry with a 3 mm plasma gap in a chamber volume of 40cm3, where the process pressure was varied from few 200 mbar to 1 bar, using pure CO2, and diluted in N2. Initial results confirmed the well-known trade-off between conversion rate (up to 60%) and energy efficiency (up to 35%) into the dissociation products, as measured downstream of the reactor system. Improving conversion rate, energy efficiency and the trade-off curve can be further accomplished by tuning the plasma operating parameters (e.g. the gas flow and system geometry). It was found that the combination of a high-power, water-cooled plasma reactor, together with electronic and waveform diagnostic, optical emission and mass spectroscopies provides a convenient experimental framework for studies on the chemical storage of fast electric power transients and surges. [ABSTRACT FROM AUTHOR]

The paper presents a computational and analytical study of GTP-based cogeneration power plants, designed to produce electrical power using low-grade heat energy obtained from liquefied natural gas (LNG). Each energy system consists of three circuits. Results of thermodynamic calculations carried out for all circuits of the considered power plants are discussed, together with a comparison in terms of efficiency, power, and energy return coefficients, taking into account various working fluids and conditions at the boundaries of circuits. [ABSTRACT FROM AUTHOR]

Chinese Green Climate Fund (GCF) is expected to launch by the government in the foreseeable future to support local governments in climate change adaption and mitigation. Lessons from experiences of international financing and allocating mechanisms provide valuable references for establishing the Chinese GCF. This study aims to explore the feasibility of several well-recognized schemes for financing and allocating the Chinese GCF among China's 30 provinces. These include: financing schemes of historical emission responsibility (HR), ability-to-pay (AP) and preference score compromises (PSC); as well as allocating schemes of carbon emissions intensity (CI), carbon emissions per capital (CC), GDP per capital (GC) and PSC. This study derives several important findings. Firstly, given different financing schemes, the coastal economically developed provinces including Shandong, Jiangsu, Guangdong, and Zhejiang would collectively shoulder most of the financing responsibility (almost 70% in total) and play central roles in climate financing. Shandong province presents high financing responsibilities mainly due to its export trades of primary products which rely on the development of high-polluted industries. Other three provinces show high financing responsibilities mainly due to the rapid growth of their industries (petrochemical, steel, building materials, electric power, etc.) for economic development. Secondly, the inland economically backward provinces including Shanxi, Ningxia, Guizhou, Xinjiang, and Gansu would be the top five largest recipients of the funds, obtaining more than 30% of total disbursements. The innovations and contributions of the present study are as follows: Firstly, this paper systematically explored the feasibility and alternative schemes for Chinese GCF for the first time. Further, it introduces PSC methods based on diversified approaches to explore suitable financing and allocating schemes. The schemes proposed would establish theoretical foundations for the Chinese GCF and would also promote the development of other kinds of financing for China and countries with similar economic features. [ABSTRACT FROM AUTHOR]

This paper presents an efficient approach using the bisection method for the solution of large-scale optimal power flow (OPF) problem. This method is proposed to overcome the major drawbacks of conventional/classical optimization techniques and the meta-heuristic techniques for solving the OPF problems. The conventional optimization techniques solve the OPF problem with less computational time, but they are not suitable for solving the problems with nonlinear/nonconvex and discrete variables. The evolutionary optimization techniques handle the nonconvex and discrete variables efficiently, but they demand high computational times. Therefore, to overcome the drawbacks of both conventional and evolutionary techniques, this paper proposes an efficient approach using the bisection method. In the bisection method, initially a generation schedule is determined, having an objective function value midway between its lower and upper bounds. Then, a load flow is performed for this solution to check the feasibility. If it is feasible, then the optimum solution lies between the midpoint and the lower bound. If it is infeasible, then it is between the midpoint and the higher bound. This concept is repeated until the optimum solution is found. Simulation results on two test systems (IEEE 30 bus and practical Indian 75 bus) are presented, and they are compared with the results of other competitive global approaches presented in the literature. The results show that the proposed approach can converge to the optimum solution and obtains the solution with high accuracy and least computational time. [ABSTRACT FROM AUTHOR]

Electric load forecasting is a fundamental business process and well-established analytical problem in the utility industry. Due to various characteristics of electricity demand series and the business needs, electric load forecasting is a classical textbook example and popular application field in the forecasting community. During the past 30 plus years, many statistical and artificial intelligence techniques have been applied to short term load forecasting (STLF) with varying degrees of success. Although fuzzy regression has been tried for STLF for about a decade, most research work is still focused at the theoretical level, leaving little value for practical applications. A primary reason is that inadequate attention has been paid to the improvement of the underlying linear model. This application-oriented paper proposes a fuzzy interaction regression approach to STLF. Through comparisons to three models (two fuzzy regression models and one multiple linear regression model) without interaction effects, the proposed approach shows superior performance over its counterparts. This paper also offers critical comments to a notable but questionable paper in this field. Finally, tips for practicing forecasting using fuzzy regression are discussed. [ABSTRACT FROM AUTHOR]

IN the trend of energy revolution, power data becomes one of the key elements of the power grid. And an advance power system with "electric power + computing power" as the core has become an inevitable choice. However, the traditional search approach based on directory query is commonly used for power grid operation data in domestic and international. The approach fails to effectively meet the user's need for fast, accurate and personalized retrieval of useful information from the vast amount of power grid data. It seriously affects the real-time availability of data and the efficiency of business-critical analytical decisions. For this reason, an intelligent retrieval approach for power grid operation data based on improved SimHash and multi-attribute decision making is proposed in this paper. This method elaborates the properties of SimHash and multi-attribute decision making algorithms. And an intelligent parallel retrieval algorithm MR-ST based on MapReduce model is designed. Finally, real time grid operation data from multiple sources are analyzed on the cloud platform for example. The experimental results show the effectiveness and precision of the method. Compared with traditional methods, the search accuracy rate, search completion rate and search time are significantly improved. Experiments show that the method can be applied to intelligent retrieval of power grid operation data. [ABSTRACT FROM AUTHOR]

Since the introduction of small-world and scale-free properties, there is an ongoing discussion on how certain real-world networks fit into these network science categories. While the electrical power grid was among the most discussed examples of these real-word networks, published results are controversial, and studies usually fail to take the aspects of network evolution into consideration. Consequently, while there is a broad agreement that power grids are small-world networks and might show scale-free behaviour; although very few attempts have been made to find how these characteristics of the network are related to grid infrastructure development or other underlying phenomena. In this paper the authors use the 70-year-long historical dataset (1949–2019) of the Hungarian power grid to perform complex network analysis, which is the first attempt to evaluate small-world and scale-free properties on long-term real-world data. The results of the analysis suggest that power grids show small-world behaviour only after the introduction of multiple voltage levels. It is also demonstrated that the node distribution of the examined power grid does not show scale-free behaviour and that the scaling is stabilised around certain values after the initial phase of grid evolution. [ABSTRACT FROM AUTHOR]

This paper presents the design and analysis of a PWM-quasi-sliding mode controller for active power factor correction (APFC) converters from a theoretical perspective. A novel design method, which contains the external ramp signal information in switching function, can be used to design a sliding mode controller with a constant switching frequency without any slope matching issues. The rigorous conclusions for reaching conditions and system stability conditions are given according to the PWM-quasi-sliding mode control theory. Three different approaches, namely conventional sliding mode control, triangular sliding mode control and PWM-quasi-sliding mode control, are compared in this paper. The simulation results show that the performance of PWM-quasi-sliding mode control agrees with the theoretical design, and this mode shows better working characteristic than conventional sliding mode control and triangular sliding mode control. [ABSTRACT FROM AUTHOR]

With the electric power grid experiencing a rapid shift to the smart grid paradigm over a deregulated energy market, Internet of Things (IoT) based solutions are gaining prominence and innovative Peer To Peer (P2P) energy trading at micro-level are being deployed. Such advancement, however leave traditional security models vulnerable and pave the path for Blockchain, an Distributed Ledger Technology (DLT) with its decentralized, open and transparency characteristics as a viable alternative. However, due to deregulation in energy trading markets, massive volumes of micro transactions are required to be supported, which become a performance bottleneck with existing Blockchain solution such as Hyperledger, Ethereum and so on. In this paper, a lightweight 'Tangle' based framework, namely IOTA (Third generation DLT) is employed for designing an energy trading market that uses Directed Acyclic Graph (DAG) based solution that not only alleviates the reward overhead for micro-transactions but also provides scalability, quantum-proof, and high throughput of such transactions at low confirmation latency. Furthermore the Masked Authentication Messaging (MAM) protocol is used over the IOTA P2P energy trading framework that allows energy producer and consumer to share the data while maintaining the confidentiality, and facilitates the data accessibility. The Raspberry Pi 3 board along with voltage sensor (INA219) used for the setting up light node and publishing and fetching data from the Tangle. The results of the obtained benchmarking indicate low confirmation latency, high throughput, system with Hyperledger Fabric and Ethereum. Moreover, the effect of transaction rate decreases when the IOTA bundle size increases more than 10. For bundle size 5 and 10 it behaves absolutely better than any other platform. The speedy confirmation time of transactions in IOTA, is most suitable for peer to peer energy trading scenarios. This study serves as a guideline for deploying, end-to-end transaction with IOTA Distributed Ledger Technology (DLT) and improving the performance of Blockchain in the energy sector under various operating conditions. [ABSTRACT FROM AUTHOR]

Smart lighting is considered an emerging trend in the global lighting industry. In terms of scale, expense, and performance, smart LED lighting applications are more advantageous. However, the input current of the power supply used for driving LEDs is more polluted due to the presence of switching devices, thereby lowering the power factor (PF). The bridge circuit of conventional DC–DC converters that use a diode bridge rectifier (DBR) as an interface between the main supply and the LED load have substantial losses and hence offers low efficiency. It also presents adverse power quality problems in the supply current resulting in poor PF. In this paper, artificial bee colony optimization algorithm-based closed loop digital proportional integral controller design and implementation of modified Type-III Bridgeless Cuk (BLCUK) LED driver are presented to obtain unity power factor and higher efficiency for smart lighting applications. MATLAB software is used to conduct the computer simulation analysis of the BLCUK converter. The experimental prototype is developed and tested using C2000 32-bit Microcontroller TMS320F28027. The digital controller (2P2Z-two poles two zeros controller) is implemented for the proposed control scheme, and the obtained experimental results are in consonance with the simulation outcomes. [ABSTRACT FROM AUTHOR]

Considering the elasticity of the real networks, the components in the network have a redundant capacity against the load, such as power grids, traffic networks and so on. Moreover, the interaction strength between nodes is often different. This paper proposes a novel nonlinear model of cascade failure in weighted complex networks considering overloaded edges to describe the redundant capacity for edges and capture the interaction strength of nodes. We fill this gap by studying a nonlinear weighted model of cascade failure with overloaded edges over synthetic and real weighted networks. The cascading failure model is constructed for the first time according to the overload coefficient, capacity parameter, weight coefficient, and distribution coefficient. Then through theoretical analysis, the conditions for stopping failure cascades are obtained, and the analysis shows the superiority of the constructed model. Finally, the cascading invulnerability is simulated in several typical network models and the US power grid. The results show that the model is a feasible and reasonable change of weight parameters, capacity coefficient, distribution coefficient, and overload coefficient can significantly improve the destructiveness of complex networks against cascade failure. Our methodology provides an efficacious reference for the control and prevention of cascading failures in many real networks. [ABSTRACT FROM AUTHOR]

This paper presents the details of exhaustive investigations on a typical Saudi distribution network showing the effectiveness of various control techniques to mitigate the voltage rise issues due to high penetration of solar photovoltaic (PV) systems. One of the major goals of Saudi Arabia future economic plans is to expand on renewable energy installations throughout the Kingdom. It is planned to generate 9.5 GW of electric power from renewable energy sources by 2023. Further, energy regulators in the Kingdom have announced policies and regulations govern the integration of small- and large-scale solar PV. However, distributed solar PV systems come with technical challenges, especially during high level of integration including grid stability, voltage rise, flickering, frequency fluctuation, and protection and coordination schemes. One issue is that the voltage profile is expected to change and rise to unacceptable level, especially with high solar PV penetration. Various voltage rise mitigation techniques investigated include active power curtailment, reactive power injection, and also a hybrid combination of these two methods. The paper reports the results of both steady-state and dynamic analyses of the Saudi distribution network at various load levels. The investigations reveal that the hybrid approach is more effective in the voltage rise mitigation. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSN) have turned into a main area for research. A sensor is a gadget that reacts and recognizes some kind of contribution from both physical and other environmental conditions, for example pressure, heat, light and so on. The yield of the sensor is, by and large, an electrical signal that is transmitted to a controller for processing. WSN can be chosen as per application demands. Smart grid is meant for efficient electricity transmission with low cost of electricity rates and high security. Accordingly, solar cells and wind turbines are the standard distributed renewable power generators. However, compared to the traditional energy production situation, it is difficult to predict the demand–supply drawback. Voltage fluctuations and grid instabilities are the main problems caused by low-voltage power grid. Extension of a smart grid is needed to find a path way for effective applications such as wireless energy management. In this paper, the researcher proposes a skilled monitoring system for power generation. The load-side power is kept on observation and the data sent to the monitoring unit. The connected solar panels are controlled based on the demand for current supply. The faulty solar panel is exposed by enabling web browser application with IoT. Every 2 s, data in the utility and generation units are sent to the web page for processing. In the experimental section a voltage of about 5 V and 25 V is obtained while variations from 0 to 5 V in the output voltage by the voltage sensor are seen. Dynamic power source solar panels are connected and disconnected based on the load capacity. Variations in dynamic load can be made in the grid. Power source can be varied according to the load present in the grid. The power source retained in the grid will be load capacity + 50% more to enable with standing sudden variations in the load. When variations in any load current vary close to 15% of the total capacity of the grid, another power source is added to the grid. Total power source is designed to the maximum load capacity, and dynamic power source is connected according to the load present in the grid. As per the result achieved by the data, it is proven that the proposed mechanism is far better than the existing traditional systems. [ABSTRACT FROM AUTHOR]

In this paper, a new method for the verification of the power-down mode of analog circuits is presented. In power-down mode, internal nodes of the circuit can be floating. These nodes can cause short-circuit paths and reliability problems due to stress. However, automatic and reliable detection of floating nodes is not straightforward, because numerical simulation is often not trustworthy in the presence of floating nodes. The presented method estimates the node voltages in power-down mode by using a voltage propagation approach based on the circuit structure. No numerical simulation is needed. The circuit is transformed to a propagation graph which models the static behavior of the circuit. The propagation graph is scanned for short-circuit paths. Experimental results demonstrate the effectiveness and efficiency of the presented method as well as common pitfalls of numerical simulation. [ABSTRACT FROM AUTHOR]

Annual power load forecasting is essential for the planning, operation and maintenance of an electric power system, which can also mirror the economic development of a country to some extent. Accurate annual power load forecasting can provide valuable references for electric power system operators and economic managers. With the development of Energy Internet and further reformation of electric power market, power load forecasting has become a more difficult and challenging task. In this paper, a new hybrid annual power load forecasting model based on LSSVM (least squares support vector machine) and MFO (Moth-Flame Optimization algorithm) is proposed, which the parameters of LSSVM model are optimally determined by the latest nature-inspired metaheuristic algorithm MFO. Meanwhile, the rolling mechanism is also employed. The forecasting results of China's annual electricity consumption indicate the proposed MFO-LSSVM model shows much better forecasting performance than single LSSVM, FOA-LSSVM (LSSVM optimized by fruit fly optimization), and PSO-LSSVM (LSSVM optimized by particle swarm optimization). MFO, as a new intelligence optimization algorithm, is attractive and promising. The LSSVM model optimized by MFO can significantly improve annual power load forecasting accuracy. [ABSTRACT FROM AUTHOR]

This paper analyzes the valuation and pricing of physical electricity delivery contracts from the viewpoint of a producer with given capacities for production and fuel-storage. Using stochastic optimization problems in discrete time with general state space, the dual problems of production problems are used to derive no-arbitrage conditions for fuel and electricity prices as well as superhedging values and prices of bilaterally traded electricity delivery contracts. In particular we take the perspective of an electricity producer, who serves contractual deliveries but avoids unacceptable losses. The resulting no-arbitrage conditions, stochastic discount factors and superhedging prices account for typical frictions like limitation of storage and production capacity and for the fact that it is possible to produce electricity from fuel, but not to produce fuel from electricity. Similarities, but also substantial differences to purely financial results can be demonstrated in this way. Furthermore, using acceptability measures, we analyze capital requirements and acceptability prices for delivery contracts, when the producer accepts some risk. [ABSTRACT FROM AUTHOR]