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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]

Effective quality management plays a pivotal role in ensuring the smooth operation of smart city systems, which have significant implications for safety, accessibility, affordability, and maintainability. Dependability of autonomous systems is of utmost importance, as achieving satisfactory levels of availability and reliability poses considerable challenges. Smart cities are characterized by interconnected sub-architectures, encompassing vehicle monitoring, sidewalk monitoring, and building monitoring, all of which need to function efficiently. Analytical models such as Petri nets, Markov chains, and fault trees are well-suited for evaluating complex scenarios in the context of smart cities. This paper presents analytical models that utilize fault tree and Markov chain techniques to assess the availability and reliability of smart city monitoring systems. The model is divided into shared and non-shared components, with non-shared components being specific to certain contextual applications, while shared components, such as data processing and electrical power, are essential for all smart city monitoring and management systems. The study underscores the ease with which the fault tree model can enhance availability by modifying failure requirements and resources. Case studies provide concrete examples of how availability improved from 95.3 to 99.8% by varying a configuration known as "KooN" in multiple components. This paper takes a comprehensive approach to evaluating the dependability of smart city architectures and contributes advancements, such as hierarchical modeling, sequential sensitivity analysis, and the "KooN" analytic method. These contributions expand the existing knowledge and methodologies in smart city dependability analysis. Moreover, this work aims to serve as a practical tool to assist smart city managers in optimizing their proposals. All modeling aspects and parameters are detailed thoroughly to enable effective implementation of the proposed approach by anyone using it. [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]

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]

As electric vehicle (EV) adoption increases, transportation services will shift dependence from liquid fuel infrastructure to electric power infrastructure. Since transportation plays a major role in disaster response and recovery, this shift in dependence has important implications for coupling electrical grids and transport resilience. The implications for the electrical grid for southwestern British Columbia, Canada are examined, motivated by this region's high EV adoption rate and the potential for a catastrophic magnitude 9.5 earthquake. A comparison of the resilience of the electrical infrastructure compared to the fuel infrastructure is provided and approaches for increasing resilience in the region for EV power supply are discussed. This paper compiles lessons learned from past large earthquakes in Chile, Japan, and New Zealand with consideration given to successes and failures. While this paper was written with a focus on southwestern British Columbia, many of the suggestions for increasing power system resilience could be applied in other seismically active locations during the transition to EVs. This paper also considers integrated disaster resilience planning for the changing transport landscape from fuel vehicles to EVs. [ABSTRACT FROM AUTHOR]

The energy consumption of Cloud–Edge systems is becoming a critical concern economically, environmentally, and societally; some studies suggest data centers and networks will collectively consume 18% of global electrical power by 2030. New methods are needed to mitigate this consumption, e.g. energy-aware workload scheduling, improved usage of renewable energy sources, etc. These schemes need to understand the interaction between energy considerations and Cloud–Edge components. Model-based approaches are an effective way to do this; however, current theoretical Cloud–Edge models are limited, and few consider energy factors. This paper analyses all relevant models proposed between 2016 and 2023, discovers key omissions, and identifies the major energy considerations that need to be addressed for Green Cloud–Edge systems (including interaction with energy providers). We investigate how these can be integrated into existing and aggregated models, and conclude with the high-level architecture of our proposed solution to integrate energy and Cloud–Edge models together. [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]

High mechanical strength surge arresters (HPCAs) are essential components for protecting electrical power systems from overvoltage surges. However, HPCAs can fail under cantilever loading conditions, which is a rare but serious event that can have significant consequences for the reliability of the power system. This paper presents a failure analysis and optimization of HPCAs based on finite element analysis (FEA). A three-dimensional FEA model was developed and used to evaluate the cantilever strength of the arrester under various design configurations. The existing design configuration with 12 insulating rods of 5.8 mm diameter was found to fail to meet the cantilever strength criteria. Therefore, the deflection values of various configurations of insulating rod diameter (5.8, 8, 10, 12, 14, and 16 mm) and number of rods (12, 18, and 14) were evaluated. The depth of the insulating rods inside the aluminum end fittings (EFs) was also varied. This work further employs a ramping method in analysis to reduce processing time and applies adhesion boundary conditions to simulate the behavior of the insulating rods and aluminum EFs. These approaches have allowed us to accurately model the behavior of the HPCA under cantilever loading conditions and investigate the failure mechanisms of the system. The FEA results showed that the cantilever strength of the HPCA could be significantly improved by increasing the diameter of the insulating rods and/or increasing the number of rods. The proposed approach is used to develop a new HPCA design with improved mechanical strength, which is validated through experimental testing. [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]

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 outdoor terminal box is the basic node of the power Internet of Things as an intermediate link between outdoor electrical equipment and indoor equipment, like measurement and control, protection, communication and other equipment. Terminal boxes and terminals need to be regularly checked on site, loop tests, transformations, and equipment replacement. Operator errors have become one of the main factors in outdoor terminal box accidents. In terms of human risk assessment of outdoor terminal boxes, few papers are involved. In order to correctly evaluate the influence of human factors on the failure of outdoor terminal boxes, the paper first analyzes the human behavior factors of outdoor terminal box operators, the common performance conditions of the CREAM (Cognitive Reliability and Error Analysis Method) model is used to analyze the human behavior mechanism and behavior reliability factors during the operation of the terminal box. Then, the SLIM (Success Likelihood Index Method) model is used to calculate the probability of human error. The proportional failure model is used to calculate the failure rate of the outdoor terminal box itself. Finally, taking a circuit breaker terminal box as an example for simulation, the probability of human error is 1.56%, the equipment failure rate is 0.84%, the risk value of the system is 10.7%, and the risk level of the system is 3. From the probabilistic perspective, it shows that human factors have a greater influence on the causes of accidents. [ABSTRACT FROM AUTHOR]

Hybrid renewable power generation becomes essential in most of electric power networks. Battery storage is commonly used in renewable energy systems (RESs) with distributed generation, such as solar and wind energy systems, to reduce power fluctuations caused by the intermittent behavior of renewable energy sources. A battery has been connected with the dc grid through a dc–dc bi-directional converter. The control scheme of the dc–dc bi-directional converter (BDC) is having two controlled loops. One is voltage-controlled loop, and another is the current-controlled loop. In this work, two-degree-of-freedom fractional order proportional integral derivative + proportional integral controller (2-DOF FOPID + PI) is proposed and applied in the voltage-controlled loop to stabilize the dc bus voltage and power flow effectively for both islanded mode and grid-connected mode. A novel meta-heuristic algorithm, i.e., modified sine cosine algorithm (m-SCA), is used to tune the controller parameters of the proposed controller. To test the performance of the modified SCA algorithm, various well-known uni-modal and multi-modal benchmark functions are taken in this paper. To confer the viability of the proposed controller, its performance is compared with other literature-based conventional controllers. This paper presents time-domain analysis, stability, and robustness test to illustrate the effectiveness of the proposed controller. MATLAB/Simulink has been used for computational work to analyze the system's efficiency. Finally, the proposed technique is validated by using OPAL-RT platform (Opal-RT-OP4510 model) with the power management of RES (PV and wind) and battery energy storage. Experimental work proved the effectiveness of the proposed m-SCA optimized 2-DOF FOPID + PI controller. [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]

China Power Grid is actively building a new energy-based ultra-high voltage grid system. Therefore, the researches on fire safety of power grid are of great importance. This paper firstly investigates the fire accident characteristics in the substation system. With the focuses on the transformer oil fires, the early detection and early warning, modification, fire monitoring and extinguishing systems of transformer oil are reviewed. It is found that the researches on flowing and jet fires should be reinforced while modified oil and pyrolysis gas detection can be applied for reducing the fire probability. Secondly, the fire risks and characteristics of cables are summarized for the transmission and distribution lines, and the methods of early warning, fire prevention and rescue are analyzed. For the wildfire threatening the transmission and distribution cables, the characteristics of wildfire and corresponding firefighting methods are reviewed. The water mist and liquid nitrogen are identified as the most effective ways of extinguishing cable fires and advanced fire detection and long-range drone fire extinguishing technologies should be improved for wildfires. Finally, the thermal runaway mechanism and fire characteristics of LIB in the energy storage system are summarized, and the difficulties in fire extinguishing are discussed. The application of the existing fire detection system in the field of LIB is proposed, and the early warning indicators for intelligent fire protection are introduced. In the future, the intelligent fire protection systems will improve the safety of energy storage systems, and efficient test platforms and reliable test standards will continue to be demanded to reduce the likelihood of thermal runaway and fire severity. [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]

In recent years, blockchain technology has generally provided a wide range of application values in various fields. However, interdisciplinary research on blockchain technology and carbon trading companies is currently rare. Based on this, this paper takes the integration of blockchain technology and carbon trading companies as the background and draws on relevant theories such as blockchain technology, carbon trading mechanisms, and major technological changes to study the influencing factors of carbon trading companies applying blockchain technology by combining theoretical deduction with an empirical test. The results show that (1) the number of companies in China's eight carbon trading pilots shows an obvious regional imbalance. Among them, more companies participated in the carbon trading pilot in Shenzhen and Beijing while less in Tianjin and Hubei. Meanwhile, the participating companies in the eight carbon trading pilots are mainly concentrated in eight industries, including electric power, petrochemical, chemical, building materials, iron and steel, nonferrous metals, papermaking, and domestic civil aviation. (2) The willingness of carbon pilot companies to use blockchain technology is stronger; the time for carbon pilot companies to learn and master blockchain technology is shorter, otherwise, the longer. Therefore, priority can be given to applying blockchain technology in carbon pilot industries with strong use willingness. (3) If more companies participate in carbon trading, the easier it is for companies to learn to use blockchain technology in the early stage. Therefore, if the pilot for the application of blockchain technology is carried out in carbon trading companies, the two carbon pilots in Shenzhen and Beijing can be given priority. This paper further enriches the relatively scarce existing interdisciplinary literature on blockchain technology and carbon trading in theory and also provides guidance for the effective application of blockchain technology by carbon trading companies in reality. [ABSTRACT FROM AUTHOR]

In this project, an architecture is implemented that can monitor and assist users in calculating their energy consumption by means of IoT technologies. It is necessary to create a system to improve and help the user in their consumption-based planning due to advances in technology. This implementation can be achieved with the use of IoT (Internet of Things) and thus ensure user convenience and comfort, which is the main goal of a smart home. These technologies involve the interoperability of the data obtained from each appliance and the location of users between the communication hardware layers specified for monitoring. This paper also provides information about cloud services, which are made available by middleware and may also include new external applications. The architecture offers details about consumption and recommends means to improve it by creating profiles which can help end users in making decisions for better optimization of the consumption rate that matches the demands of the customers or the electric power utility. This paper concludes that this architecture is very promising and new and viable technologies can be implemented to make significant improvements for the residents and electric power utilities. [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]

Green computing is an important factor to ensure the eco-friendly use of computers and their resources. Electric power used in a computer converts into heat and thus, the system takes fewer watts ensuring less cooling. This lower energy consumption allows to be less costly to run as well as reduces the environmental impact of powering the computer. One of the most challenging problems for the modern green supercomputers is the reduction of current power consumptions. Consequently, regular conventional interconnection networks also show poor cost performance. On the other hand, hierarchical interconnection networks (like-3D-TTN) can be a possible solution to those issues. The main focus for this paper is the estimation of power usage at the on-chip level for 3D-TTN with the various other networks along with the analysis of static network performance. In our analysis, 3D-TTN requires about 32.48% less router power usage at the on-chip level and can also achieve near about 21% better diameter performance as well as 12% better average distance performance than the 5D-Torus network. Similarly, it also requires only about 14.43% higher router power usage; however, can achieve 23.21% better diameter performance and 26.3% better average distance than recent hierarchical interconnection network- 3D-TESH. The most attractive feature of this paper is the static hop distance parameter and per watt analysis (power-performance). According to our power-performance results, 3D-TTN can also show better result than the 3D-Mesh, 2D-Mesh, 2D-Torus and 3D-TESH network even at the lowest network level. Moreover, this paper is also featured with the static effectiveness analysis, which ensures cost and time efficiency of 3D-TTN. [ABSTRACT FROM AUTHOR]

The electric energy mainly comes from thermal power generation fueled by electric coal, and the selection of electric coal supplier is of great practical significance for the development of electric power enterprises. In this paper, the mechanism of supplier selection in electric coal procurement is designed from a perspective of sustainability. Concretely, eleven evaluation indexes from three aspects of economy, environment, and society are selected to construct a new evaluation index system for selecting sustainable electric coal suppliers. Based on this index system, a new method of supplier selection in electric coal procurement based on 2-tuple correlation coefficient analysis is proposed. In this method, considering that the evaluation index values have the features of multi-source heterogeneous data, i.e., precise real number, interval number, and fuzzy linguistic variables coexist, all index values are converted into 2-tuples. Then, a 2-tuple deviation maximization method is proposed to determine the weight of each evaluation index, and a new method of 2-tuple correlation coefficient analysis is proposed to select sustainable electric coal suppliers. Moreover, the effectiveness and feasibility of the model are highlighted by an application example of selecting the electric coal suppliers. Combined with the development status of electric power industry and the research results of this paper, several countermeasures and suggestions are provided on how to formulate the optimal procurement strategy of electric coal for electric power enterprises and how to improve the competitiveness for electric coal suppliers. [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]

In today's constantly advancing economy, fast and efficient load frequency control (LFC) schemes are imperative for stable power systems operation, whether conventional or new. Despite recent advances in this domain, professional engineers, to this day, face significant obstacles in dealing with parametric uncertainty and the rejection of external disturbances. To ensure high-quality, resilient, and consistent electrical power, the developed controllers must operate efficiently, i.e., counteract frequency and tie-line power deviations. In light of this, the current study presents a novel strategy employing several machine learning algorithms to remedy the LFC dilemma, estimating the optimal controller gain values in a real-time environment. A comprehensive case study incorporating random load perturbations exemplified the trained controllers' accuracy, robustness, and adaptability. The proposed online controllers, integrated into emerging power systems with several adjoining regions, renewable sources, and nonlinearities, outperform benchmark procedures. A rank-based statistical analysis implementing the Friedman test reveals Random Forest to be the most effective of the studied algorithms in terms of providing the lowest integral-criteria error values while preserving the minimal peak overshoot, undershoot, and settling duration. This paper demonstrates the significant potential of the suggested framework in addressing the LFC predicament in relevant sectors. [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]

Nuclear batteries are devices that provide electrical power by converting the energy of radioactive decays. Their full operational potential depends on the actual limits set by the specific power (W/g) released by a radioisotope. This paper analyzes the main features of α-, β‒- or γ-emitting radioisotopes most qualified to run nuclear batteries, and provides updated values of specific power released by their decays as well as specific total energy (kWh/g) supplied over a given working period. When it is the case, the contribution coming from the daughter radionuclide is also taken into account. [ABSTRACT FROM AUTHOR]

Today, increasing communication of Internet of Things (IoT) devices, wearable sensors, healthcare applications and cloud providers provides power and energy consumption for high processing personal data and healthcare records. Cloud-edge data centers are processing enormous amount of electrical power resulting in high performance computing. One of the important challenges in this problem is Virtual Machine (VM) service placement that attempts to enhance energy management of VMs to cloud-edge service providers dynamically to support Service Level Agreement (SLA) metrics in IoT systems. Service placement is a very important issue because if VMs are not confident in the SLA of their critical data, IoT applications will not want to use existing resources safety. Providing a way to increase the Quality of Service (QoS) factors and energy efficiency of the service placement in the IoT environment is an important and critical issue because the use of IoT devices and wearable sensors increases energy consumption in human life in smart contracts. Therefore, this paper presents a hybrid Genetic algorithm and social spider optimization (GA-SSO) algorithm for an energy-aware service placement model in the IoT to manage data congestion and system safety. After conducting studies and comparisons, the accuracy and superiority of the proposed model were established. Experimental results show that the energy consumption with the proposed GA-SSO algorithm can be reduced 24% and we can achieve to the performance of QoS factors with fitness function 88% with compare to the other meta-heuristic algorithms. [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]

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]

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]

Fault diagnosis and detection in electrical power systems need a development of new and robust supervision structures. In the last years, different intelligent monitoring methods have been successfully proposed to deal with the problem of fault diagnosis in power transmission lines. In this work, a new hybrid strategy called FFT-FL combining Fuzzy Logic (FL) approach with Fast Fourier Transform (FFT) is proposed and applied to fault diagnosis in power line network. The elaborated fault detection structure consists of indicating whether the electrical transmission is working correctly or a fault has occurred with an effective isolation step to determine the faulty zone in the line. Whereas, an identification step consists of determining faulty phase thus fault classification in the studied line network. The novel proposed algorithm (FFT-FL) is used to improve the fault diagnosis response time and to decouple between faults and disturbances. In this paper, a comparative study is presented between the two intelligent methods for detection, isolation and identification of faults using only FL and the hybrid FFT-FL structure. The obtained simulation results verify the effectiveness and the correctness of the proposed fault method for all types of faults in the power line networks and in different zones. [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]

In this paper, three photovoltaic (PV) cooling systems are examined. The three cooling systems are (1) a PV frontside passive air (FPA) cooling system that relies on the chimney effect of air to cool the PV module, (2) a PV frontside active water (FAW) cooling where water flows in frontside of the PV panel, and (3) a PV backside active water (BAW) cooling system where water flows in a heatsink (collector) attached to the backside of the PV module. While comparing to the standalone PV, the FPA, FAW and BAW systems have cooled the PV surface temperature by 2.1, 22.4 and 17.8 °C, respectively. The FPA and BAW systems improved the PV electric efficiency by 0.84 and 6.86%, respectively; while, the FAW system degraded the PV efficiency by 26.27 % . The spectrometer measurement showed that the plexiglass and water thickness significantly lower the transmission of ultraviolet and visible light waves to the PV module. In contrast, the FAW system produced water with higher thermal content than that of the BAW system. The results show that to maximize electrical power output, BAW system is recommended, while to maximize thermal energy collection, FAW system is recommended. [ABSTRACT FROM AUTHOR]

Nowadays, the utilization of Flexible Alternating Current Transmission System (FACTS) devices remains a better alternative for improving Available Transfer Capability (ATC), and it further minimizes the system loss in aggressive electrical power systems. It could minimize the cost of the new transmission line construction and also enhance the utilization rate. This paper introduces a new optimization-assisted ATC enhancement model by determining the optimal placement and compensation level of a Thyristor Controlled Series Capacitor (TCSC) device. As a novelty, a unique Improved Sea Lion Optimization (I-SLnO) model is established, which is an improved form of the conventional Sea Lion Optimization (SLnO) model. The evaluation is performed in IEEE-14 & IEEE-39 test bus systems to analyze the effectiveness of the suggested approach in terms of convergence analysis, ATC enhancement, and so on. [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]

This work analyzes the use of artificial neural networks in the short-term streamflow forecasting for large interconnected hydropower systems. The state-of-the-art optimization algorithms, activation functions, and weight initialization techniques are investigated together with classic methods. We present an algorithm to define the neural network inputs in large hydrosystems and apply it to create models for 55 major hydro plants located in the Paraná Basin, which contribute to more than 30% of the total power generated in Brazil. The paper also compares the performance of the neural networks with the hydrological models that are currently used by the independent system operator to define the dispatch of the electric power generators. Our results show that, overall, the neural network models provide more accurate forecasts than the hydrological models used by the Brazilian System Operator. Finally, the paper discusses the contributions of historical rainfall information in the forecasting of streamflow while using neural network models. [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]

Wireless sensors have been developed rapidly, while their energy supply components are relatively backward since the beginning of the twenty-first century. This paper proposes a symmetrical V-shaped micro-piezoelectric energy harvester (SV-MPEH) based on PZT-5H, which is used to supply energy to sensors that detect ambient temperature. Firstly, the finite element model and the electromechanical coupling model are established. Secondly, the SV-MPEH adopts parametric design to ensure steady-state output power. Then, the output performance of the SV-MPEH is simulated when the initial temperature is 373 K under the accelerations of 0.5 g, 1 g, and 1.5 g, respectively. Finally, three sets of steady-state output powers are obtained by using two access methods (Type I and Type II) of piezoelectric components. The simulation results indicate that the output power of the SV-MPEH is nearly 20% higher than that of conventional cantilever harvester under the same simulation parameters. In addition, the power density of the SV-MPEH shows a different upward trend through the two access methods (Type I and Type II) of piezoelectric sheets, and Type I exhibits a higher growth rate than Type II. [ABSTRACT FROM AUTHOR]

Clean energy complementary system can reduce environmental pollution effectively and is considered as a future energy development direction. In this paper, an innovative solar-nuclear thermally coupled power and desalination plant for electricity and freshwater productions is proposed. As solar power and nuclear power are combined, this multi-energy system is a clean energy system and basically has no emissions of soot, sulfur oxides, carbon dioxide, and nitrogen oxides. The operating behavior assessment results of the multi-energy system show that the power generation and freshwater production systems can operate synergistically. The electric power and corresponding efficiency of the multi-energy system are 290.7 MW and 38.2%, in which the solar proportion is about 38.1%. The daily freshwater production of the multi-energy system is 3761.3 t. The economic assessment results reveal that the levelized costs of electricity and freshwater of the multi-energy system are 0.361 yuan/(kWh) and 1.645 yuan/t. The environmental protection analysis results show that in contrast with a coal-fired system, the annual emission reductions of soot, sulfur oxides, carbon dioxide, and nitrogen oxides of the multi-energy system are 7350.94 t, 12,634.42 t, 513,034.14 t, and 11,945.28 t, revealing a significant environmental protection performance. [ABSTRACT FROM AUTHOR]

Now a days, electric power infrastructure is an essential section of the world due to the increase in power demand and industrialization. The smart grid is also one of the profoundly evolved innovations, which influences the synchronization between demand and renewable energy reactions. The smart grids contain many operations with power calculations such as smart functions, assurance, and control techniques to provide steadiness and proficiency to the system performance. However, the quality of power such as voltage deviation minimization, sag/swell, power loss minimization, and Total Harmonic Distortion (THD) appear to be the major issue. Therefore, in this paper, a novel Generalized Approximate Reasoning Intelligent Control along with Multi-objective African Buffalo Optimization is proposed to control the imperatives of the smart grid. In the grid, current controllers are upgraded by the proposed Optimal Pseudospectral Bang Bang Control technique, and voltage controllers are improved by the proposed Bessel Filter Sallen Key Topology. The simulation of the proposed method is actualized with MATLAB/Simulink. Consequently, the projected results are compared with the traditional control techniques and the outcomes show that the projected replica improved system efficiency concerning power quality problems in terms of reduced 14 MW of power loss and 2.18% of THD. [ABSTRACT FROM AUTHOR]

The Heihe Water Diversion Project in Zhouzhi County, Shaanxi Province is a "lifeline" engineering project that supplies water as well as electric power to Xi'an City, China. This canyon-type reservoir is located at the mouth of the Heihe River on the northern flank of the Qinling Mountain. Slope stability of the reservoir bank is one of the critical geological engineering problems, among which the toppling rock slope of Shuimengou is a major threat to the dam and downstream residents. The toppling rock mass was formed by downcutting of the river, and the hard thin-layer metamorphic schist gradually bent under the action of gravity. Monitoring data in recent decade showed that the process of toppling continued slowly. Under the erosion of the reservoir water the stability of the toppling slope may deteriorate in the coming time. Hence, it is essential to predict the stability of the slope and to give a proposal for mitigation. For this purpose, this paper simulates and analyzes the deforming process of the toppling slope in geological history using the discontinuous deformation analysis (DDA) method. Furthermore, in consideration of the reservoir erosion at the foot of the slope the future deformation-failure of the slope is also simulated. Based on the result, a reasonable counter measure is proposed for stabilizing the slope. [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]