New insights on thermal ageing of electrical insulating oils as revealed from photoluminescence and absorption spectroscopy

Recently,significant efforts have been exerted to replace mineral oil with environmentally friendly oils due to safety and environmental issues.However,there is a need to clarify the physical mechanisms behind the ageing impact of these oils.The authors use advanced optical spectroscopy techniques in correlation with dielectric measurements to understand the ageing processes in environmentally friendly oils as well as mineral oil.Firstly,different samples of environmentally friendly oils and mineral oil were utilised to investigate the ageing mechanism.The samples were subjected to different ageing periods using a thermal accelerated ageing process.Secondly,the severity of the produced byproducts due to the oil degradation is examined based on several measured properties representing macroscopic and microscopic categories.The macroscopic category was evaluated through dielectric properties,including breakdown voltage,dielectric permittivity,and dissipation factor.The microscopic category,on the other hand,was assessed using techniques such as ultraviolet-visible absorption spectroscopy and photoluminescence spectroscopy.These techniques enabled a deep understanding of the molecular-level changes occurring in the oil under ageing conditions,thereby getting new insights into oil ageing mechanisms.It is worth mentioning that natural ester oil demonstrated the most favourable performance across various properties under ageing conditions.

Sizing of STATCOM to Enhance Voltage Stability of Power Systems for Normal and Contingency Cases

The electric power infrastructure that has served huge loads for so long is rapidly running up against many limitations. Out of many challenges it is to operate the power system in secure manner so that the operation constraints are fulfilled under both normal and contingent conditions. Smart grid technology offers valuable techniques that can be deployed within the very near future or which are already deployed nowadays. Flexible AC Transmission Systems (FACTS) devices have been introduced to solve various power system problems. In literature, most of the methods proposed for sizing the FACTS devices only consider the normal operating conditions of power systems. Consequently, some transmission lines are heavily loaded in contingency case and the system voltage stability becomes a power transfer-limiting factor. This paper presents a technique for determining the proper rating/size of FACTS devices, namely the Static Synchronous Compensator (STATCOM), while considering contingency cases. The paper also verifies that the weakest bus determined by eigenvalue and eigenvectors method is the best location for STATCOM. The rating of STATCOM is specified according to the required reactive power needed to improve voltage stability under normal and contingency cases. Two case system studies are investigated: a simple 5-bus system and the IEEE 14-bus system. The obtained results verify that the rating of STATCOM can be determined according to the worst contingency case, and through proper control it can still be effective for normal and other contingency cases.

Design and Optimization of Interior Permanent Magnet(IPM)Motor for Electric Vehicle Applications

This paper explores some design parameters of an interior permanent magnet synchronous motor that contribute to enhancing motor performance.Various geometry parameters such as magnet dimension,machine diameter,stator teeth height,and number of poles are analyzed to compare overall torque,power,and torque ripples in order to select the best design parameters and their ranges.Pyleecan,an open-source software,is used to design and optimize the motor for electric vehicle applications.Following optimization with Non-dominated Sorting Genetic Algorithm(NSGA-Ⅱ),two designs A and B were obtained for two objective functions and the corresponding torque ripples values of the design A and B were later reduced by 32%and 77%.Additionally,the impact of different magnet grades on the output performances is analyzed.

跟网型和构网型逆变器的阻抗无源化方法综述

相比传统同步机主导的电力系统,由并网逆变器所主导的新能源并网发电系统动态特性发生了根本性变化。近年,国内外报道了多次新能源并网发电系统振荡事件,振荡现象具有宽频域特征,动态行为具有非线性、时变性和复杂性。并网逆变器的端口阻抗无源性是保证并网发电系统稳定的充分条件,适用于复杂电网下的稳定性优化。文中针对跟网型和构网型逆变器,分别从控制器优化设计、串并联虚拟阻抗和其他无源化方法这三个方面,对两类逆变器的中高频阻抗无源化改善方法进行了总结和梳理,最后探讨了当前研究的不足与现存的挑战。

Robust Position Observer for Sensorless Direct Voltage Control of Stand-Alone Ship Shaft Brushless Doubly-Fed Induction Generators

The aim of this paper is to investigate an adaptive sensorless direct voltage control(DVC)strategy for the stand-alone ship shaft brushless doubly-fed induction generators(BDFIGs).The proposed new rotor position observer using the space vector flux relations of BDFIG may achieve the desired voltage control of the power winding(PW)in terms of magnitude and frequency,without any speed/position sensors.The proposed algorithm does not require any additional observers for obtaining the generator speed.The proposed technique can directly achieve the desired DVC based on the estimated rotor position,which may reduce the overall system cost.The stability analysis of the proposed observer is investigated and confirmed with the concept of quadratic Lyapunov function and using the multi-model representation.In addition,the sensitivity analysis of the presented method is confirmed under different issues of parameter uncertainties.Comprehensive results from both simulation and experiments are realized with a prototype wound-rotor BDFIG,which demonstrate the capability and efficacy of the proposed sensorless DVC strategy with good transient behavior under different operating conditions.Furthermore,the analysis confirms the robustness of the proposed observer via the machine parameter changes.

Optimal Scheme with Load Forecasting for Demand Side Management (DSM) in Residential Areas

Utilities around the world have been considering Demand Side Management (DSM) in their strategic planning. The costs of constructing and operating a new capacity generation unit are increasing everyday as well as Transmission and distribution and land issues for new generation plants, which force the utilities to search for another alternatives without any additional constraints on customers comfort level or quality of delivered product. De can be defined as the selection, planning, and implementation of measures intended to have an influence on the demand or customer-side of the electric meter, either caused directly or stimulated indirectly by the utility. DSM programs are peak clipping, Valley filling, Load shifting, Load building, energy conservation and flexible load shape. The main Target of this paper is to show the relation between DSM and Load Forecasting. Moreover, it highlights on the effect of applying DSM on Forecasted demands and how this affects the planning strategies for utility companies. This target will be clearly illustrated through applying the developed algorithm in this paper on an existing residential compound in Cairo-Egypt.

Extensions to the Finite Element Technique for the Magneto-Thermal Analysis of Aged Oil Cooled-Insulated Power Transformers

It is well known that the hot spot temperature represents the most critical parameter identifying the power rating of a transformer. This paper investigates the effect of the degradation of core magnetic properties on temperature variation of aged oil-cooled transformers. Within this work, 2D accurate assessment of time average flux density distribution in an oil insulated-cooled 25 MVA transformer has been computed using finite-element analysis taking into account ageing and stress-induced non-uniform core permeability values. Knowing the core material specific loss and winding details, local core and winding losses are converted into heat. Based upon the ambient temperature outside the transformer tank and thermal heat transfer related factors, the detailed thermal modeling and analysis have then been carried out to determine temperature distribution everywhere. Analytical details and simulation results demonstrating effects of core magnetic properties degradation on hot spot temperatures of the transformer’s components are given in the paper.

Reliability Evaluation of Distribution Systems under <i>μ</i>Grid-Tied and Islanded <i>μ</i>Grid Modes Using Monte Carlo Simulation

Reliability evaluation of distribution networks under grid-tied and islanded μ grid modes is presented. The Monte Carlo simulation (MCS) algorithm is applied to a modified RBTS Bus 2 distribution network. The network includes three types of distributed energy resources, namely, solar photovoltaic (PV), wind turbine (WT), and diesel turbine generator (DTG). These distributed generators contribute to supply part of the load during grid-connected mode, but supply 100% of the load in the islanded μ grid mode. A storage system is included to decrease the peak load since the peak of the output power of the PV’s and the peak load do not match time wise in most load profiles. The impact of implementing renewable distributed generation, storage systems, and conventional generation on the reliability of distribution network is studied. This study shows that the penetration of distributed generations can improve the reliability indices of the distribution network.

A Transmission Line Fault Classification Approach by Support Vector Machines

This paper presents an approach for shunt faults detection and classification in transmission line using Support Vector Machine （SVM）. The paper compares between using three line post-fault current samples for one-half cycle and one-fourth cycle from the inception of the fault as inputs for SVM. Two SVMs are used, first SVMabc is used for faulty phase detection and second SVMg is used for ground detection. SVMs with polynomial kernel with different degrees are used to obtain the best classification score. The classification test results show that the proposed method is accurate and reliable.

Economic Dispatch with Convex and Non-Convex Fuel Cost Functions Including Line Losses Using Pattern Search

This article presents an application of generalized pattern search （PS） algorithm to solve economic load dispatch （ELD） problems with convex and non-convex fuel cost objective functions. Main objective of ELI） is to determine the most economic generating dispatch required to satisfy the predicted load demands including line losses. Relaxing various equality and inequality constraints are considered. The unit operation minhnum/maximum constraints, effects of valve-point and line losses are considered for the practical applications. Several case studies were tested and verified, which indicate an improvement in total fuel cost savings. The robustness of the proposed PS method have been assessed and investigated through intensive comparisons with reported results in recent researches. The results are very encouraging and suggesting that PS may be very useful tool in solving power system ELD problems.

Dissolved gas analysis and dissipation factor measurement of mineral oil-based nanofluids under thermal and electrical faults

Mineral oil is the most frequent insulating liquid used in oil-immersed transformers for electrical insulation and heat dissipation.However,oil-based nanofluids are becoming more popular in scientific research as they have proved to have better dielectric and thermal characteristics.When applying these nanofluids into actual transformers,they would be exposed to thermal and electrical stresses.Thus,The aim of the authors is to investigate the generation pattern of dissolved gases in nanofluids under thermal and electrical faults and to assess the applicability of traditional Dissolved Gas Analysis(DGA)techniques if oil-based nanofluids are used in transformers.Oil-based nanofluid samples were prepared using a magnetic stirrer and an ultrasonic homogeniser and then subjected to simulated thermal and electrical faults in the laboratory using properly sealed test cells.Three types of metal oxides,Silicon dioxide,Titanium dioxide,and Aluminium oxide nanoparticles,have been used to prepare nanofluids with 0.02 g/L and 0.04 g/L concentrations.The gases released and dissolved into oil due to the simulated faults were analysed and compared to traditional mineral oil as a benchmark.The dielectric dissipation factor was obtained and analysed for all samples.According to the findings,the presence and concentration of nanoparticles were shown to influence the amount of gases produced.As a result,this research is crucial in guaranteeing that traditional DGA techniques can be employed in transformers that use oil-based nanofluids.

Photovoltaic Models Parameters Estimation Based on Weighted Mean of Vectors

Renewable energy sources are gaining popularity,particularly photovoltaic energy as a clean energy source.This is evident in the advancement of scientific research aimed at improving solar cell performance.Due to the non-linear nature of the photovoltaic cell,modeling solar cells and extracting their parameters is one of the most important challenges in this discipline.As a result,the use of optimization algorithms to solve this problem is expanding and evolving at a rapid rate.In this paper,a weIghted meaN oF vectOrs algorithm(INFO)that calculates the weighted mean for a set of vectors in the search space has been applied to estimate the parameters of solar cells in an efficient and precise way.In each generation,the INFO utilizes three operations to update the vectors’locations:updating rules,vector merging,and local search.The INFO is applied to estimate the parameters of static models such as single and double diodes,as well as dynamic models such as integral and fractional models.The outcomes of all applications are examined and compared to several recent algorithms.As well as the results are evaluated through statistical analysis.The results analyzed supported the proposed algorithm’s efficiency,accuracy,and durability when compared to recent optimization algorithms.

Allocation and sizing of reactive power compensators considering PV power and load demand uncertainty using beetle-antenna grey wolf optimization

Distributed photovoltaic(PV)systems play an important role in supplying many recent microgrids.The absence of reactive power support for these small-scale PV plants increases total microgrid losses and voltage-instability threats.Reactive power compensations(RPCs)should be integrated to enhance both microgrid losses and voltage profiles.RPC planning is a non-linear,complicated problem.In this paper,a combined RPC allocation and sizing algorithm is proposed.The RPC-integrating buses are selected using a new adaptive approach of loss sensitivity analysis.In the sizing process,the uncertainties in PV power and load demand are modelled using proper probability density functions.Three simulation techniques for handling uncertainties are compared to define the accurate and fast accurate method as follows:Monte Carlo simulation(MCS),scenario tree construction and reduction method,and point estimation method(PEM).The load flow equations are solved using the forward-backward sweep method.RPCs are optimally sized using the beetle-antenna-based strategy with grey wolf optimization(BGWO)to overcome the local minima problem that appeared in the other pre-proposed methods.Results have been compared using particle swarm optimization and conventional GWO.The proposed model is verified using the IEEE 33 radial bus system.The expected power loss has been reduced by 22% and 31% using compensation of 26% and 44%,respectively.The results obtained prove that the BGWO optimal power flow and PEM to handle the uncertainty can significantly reduce the computation time with sufficient accuracy.Under the study conditions,PEM reduces the computation time to 4 minutes compared with 4 hours for MCS,with only a 3% error compared with MCS as an uncertainty benchmark method.

Impacts of multiple demand-side management strategies on microgrids planning:a literature survey

Demand-side management(DSM)schemes play a crucial role in managing renewable energy generation and load fluctuations by uti-lizing demand-response programmes(DRPs).This paper aims to provide a detailed overview of DRPs that help microgrid operators to keep costs and reliability within acceptable ranges.Additionally,this review paper provides a detailed economic load model for DRPs based on initial load,demand-response(DR)incentive,DR penalty and elasticity coefficients.This article also aims to guide researchers in identifying research gaps in DSM applications in microgrids by comparing various DSM schemes from different countries and regions in terms of DSM strategies,objective functions and optimization techniques.Furthermore,this study analyses the impact of DRPs on microgrid configuration from the perspective of utilities and customers,considering technical and economic performance metrics.As a result,it can be concluded that none of the studied cases provides models or guidelines for choosing appropriate DSM schemes that consider different consumer interests or load-type features.Furthermore,a few researchers have addressed the features of a modern price-based DR strategy,renewable generation-based dynamic pricing DR,which offers higher customer satisfaction than traditional DRPs.

Sensored and sensorless scalar-control strategy of a wind-driven BDFRG for maximum wind-power extraction

This paper presents a scalar volt per hertz(V/f)control technique for maximum power tracking of a grid-connected wind-driven brushless doubly fed reluctance generator(BDFRG).The proposed generator has two stator windings namely;power winding,directly connected to the grid and control winding,connected to the grid through a bi-directional converter.In order to enhance the performance of the proposed scalar-control strategy,a soft starting method is suggested to avoid the over-current of the bi-directional converter.Moreover,the capability of generator speed estimation for sensorless control is also studied.The capability of the proposed scalar-control technique is validated using a sample of simulation results.In addition,the presented simulation results ensure the effectiveness of the proposed control strategy for maximum wind-power extraction under windspeed variations.Furthermore,the results show that the estimated generator speed is in a good accordance with the actual generator speed which supports sensorless control capability.

A New Transient Impedance-Based Algorithm for Earth Fault Detection in Medium Voltage Networks

This paper presents a new earth-fault detection algorithm for unearthed （isolated） and compensated neutral medium voltage （MV） networks. The proposed algorithm is based on capacitance calculation from transient impedance and dominant transient frequency. The Discrete Fourier Transform （DFT） method is used to determine the dominant transient frequency. The values of voltage and current earth modes are calculated in the period of the dominant transient frequency, then the transient impedance can be determined, from which we can calculate the earth capacitance. The calculated capacitance gives an indication about if the feeder is faulted or not. The algorithm is less dependent on the fault resistance and the faulted feeder parameters; it mainly depends on the background network. The network is simulated by ATP/EMTP program. Several different fault conditions are covered in the simulation process, different fault inception angles, fault locations and fault resistances.

Effective participation of wind turbines in frequency control of a two-area power system using coot optimization

In this paper,load frequency control is performed for a two-area power system incorporating a high penetration of renewable energy sources.A droop controller for a type 3 wind turbine is used to extract the stored kinetic energy from the rotating masses during sudden load disturbances.An auxiliary storage controller is applied to achieve effec-tive frequency response.The coot optimization algorithm(COA)is applied to allocate the optimum parameters of the fractional-order proportional integral derivative(FOPID),droop and auxiliary storage controllers.The fitness function is represented by the summation of integral square deviations in tie line power,and Areas 1 and 2 frequency errors.The robustness of the COA is proven by comparing the results with benchmarked optimizers including:atomic orbital search,honey badger algorithm,water cycle algorithm and particle swarm optimization.Performance assessment is confirmed in the following four scenarios:(i)optimization while including PID controllers;(ii)optimization while including FOPID controllers;(iii)validation of COA results under various load disturbances;and(iv)validation of the proposed controllers under varying weather conditions.

Evaluation of On-Line MPPT Algorithms for PV-Based Battery Storage Systems

This paper presents a novel Simulink models with an evaluation study of more widely used On-Line Maximum Power Point tracking(MPPT)techniques for Photo-Voltaic based Battery Storage Systems(PV-BSS).To have a full comparative study in terms of the dynamic response,battery state of charge(SOC),and oscillations around the Maximum Power Point(MPP)of the PV-BSS to variations in climate conditions,these techniques are simulated in Matlab/Simulink.The introduced methodologies are classified into two types;the first type is conventional hill-climbing techniques which are based on instantaneous PV data measurements such as Perturb&Observe and Incremental Conductance techniques.The second type is a novel proposed methodology is based on using solar irradiance and cell temperature measurements with pre-build Adaptive Neuro-Fuzzy Inference System(ANFIS)model to predict DC–DC converter optimum duty cycle to track MPP.Then evaluation study is introduced for conventional and proposed On-Line MPPT techniques.This comparative study can be useful in specifying the appropriateness of the MPPT techniques for PV-BSS.Also the introduced model can be used as a valued reference model for future research related to Soft Computing(SC)MPPT techniques.A significant improvement of SOC is achieved by the proposed model and methodology with high accuracy and lower oscillations.

A New Approach for Converting Renewable Energy to Stable Energy

A renewable energy plant which relies on wind speed or solar insolation is unreliable because of the stochastic nature of weather patterns. It is theorized that by using multiple renewable energy plants in separate areas of a region, the different weather conditions might approach a probabilistically independent relationship. The goal of this paper is to utilize the power system technology to help disseminate wind and solar power systems to get a stable energy. A new approach to get appropriate stable energy is achieved by using the interrupted energy that obtained from wind farm and solar insolation. This is achieved by lifting water to a higher level with appropriate pumps and storing it in the form of potential energy. Then a stable energy is obtained by reliving water to the lower level. In this paper, the efficiency obtained from the renewable energy is compared with that obtained from traditional ones. An experimental model to simulate the process of converting the renewable energy to a stable energy is presented. The obtained results from experimental model explained that the renewable energy can be converted to a stable one with high efficiency.

Control Scheme of Hybrid Wind-Diesel System with SMES Using NSGA-II

Robust control approach of hybrid wind-diesel power system is proposed in this paper. PID （proportional integral derivative） controller is designed in the blade pitch system of wind turbine to improve the system dynamic performance. Furthermore, to minimize the system oscillations, SMES （super-conducting magnetic energy storage） with first order lead-lag controller is implemented to supply and absorb active power quickly trying to reach power generation/demand balance and thereby control system frequency. Minimization of frequency and wind output power deviations are considered as two objective functions for the PID controller of wind turbine. Also, mitigating frequency and diesel output power deviations are presented as two objective functions of the lead-lag controller of SMES. NSGA-II （modified version of non-dominated sorting genetic algorithm） is used to tune the controllers＇ parameters to get an optimal response. The effectiveness and robustness of the proposed control technique are investigated under different operating conditions using Matlab environment. The simulation results confirm the ability of the controllers to damp all frequency and output powers fluctuations and enhance the stability and reliability of the hybrid power system.