Migratable Power System Transient Stability AssessmentMethod Based on Improved XGBoost

The data-driven transient stability assessment(TSA)of power systems can predict online real-time prediction by learning the temporal features before and after faults.However,the accuracy of the assessment is limited by the quality of the data and has weak transferability.Based on this,this paper proposes a method for TSA of power systems based on an improved extreme gradient boosting(XGBoost)model.Firstly,the gradient detection method is employed to remove noise interference while maintaining the original time series trend.On this basis,a focal loss function is introduced to guide the training of theXGBoostmodel,enhancing the deep exploration of minority class samples to improve the accuracy of the model evaluation.Furthermore,to improve the generalization ability of the evaluation model,a transfer learning method based on model parameters and sample augmentation is proposed.The simulation analysis on the IEEE 39-bus system demonstrates that the proposed method,compared to the traditional machine learning-based transient stability assessment approach,achieves an average improvement of 2.16%in evaluation accuracy.Specifically,under scenarios involving changes in topology structure and operating conditions,the accuracy is enhanced by 3.65%and 3.11%,respectively.Moreover,the model updating efficiency is enhanced by 14–15 times,indicating the model’s transferable and adaptive capabilities across multiple scenarios.

Modeling the System for Hybrid Renewable Energy Using Highly Efficient Converters and Generator

High-efficient isolated DC/DC converters with a high-efficiency synchronous reluctance generator(SRG)are the ultimate solutions in DC microgrid systems.The design and modeling of isolated DC/DC converters with the performance of SRG are carried out.On the generator side,reactive and active powers are used as pulse width modulation(PWM)control variables.Further,the flux estimator is used.Three-phase PWM rectifier is used by applying space vector modulation(SVM)with a constant switching frequency for direct power control.Further,the paper also includes the experimental validation of the results.The paper also proposes that highly efficient power converters and synchronous reluctance generators are required to achieve high performance for hybrid renewable energy systems applications.

Application of artificial intelligent systems for real power transfer allocation

The application of various artificial intelligent(AI) techniques,namely artificial neural network(ANN),adaptive neuro fuzzy interface system(ANFIS),genetic algorithm optimized least square support vector machine(GA-LSSVM) and multivariable regression(MVR) models was presented to identify the real power transfer between generators and loads.These AI techniques adopt supervised learning,which first uses modified nodal equation(MNE) method to determine real power contribution from each generator to loads.Then the results of MNE method and load flow information are utilized to estimate the power transfer using AI techniques.The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of various AI methods compared to that of the MNE method.

Mitigation of Low Frequency Oscillations by Optimal Allocation of Power System Stabilizers: Case Study on MEPE Test System

The increases in power network and weak tie-line have led power system oscillation problems. To improve the oscillatory stability, installing the power system stabilizer (PSS) with optimal allocation is considered due to excessive cost. This paper recommends the suitable PSS locations by using eigenvalue analysis and participation factor to enhance the system oscillation damping. The effects of installed PSSs in damping local and inter-area modes of oscillations are confirmed through time domain simulation results. The effectiveness of proposed approach is tested and validated on MEPE test system. Robustness of stabilizers against dynamic response of generator speed deviation, rotor angle deviation, and response of mechanical power are observed to access the performances of PSSs.

Comparison of Experimental and Theoretical Output Power of Grid Connected Photovoltaic System in Super Mega Factory

In this paper, the performance of grid connected PV system that is installed in Super Mega Factory is presented. The output parameters of 4 kW PV is collected and analyzed. Then, according to the results the weak points of the system were found and the theoretical output power was compared. After that we try to get the maximum output power making the correction of collector angle and place suitable panel position.

Allocation of Hybrid Distributed Generations and Energy Management in Radial Electrical Systems

This paper presents a method for optimal sizing of a Micro grid connected to a hybrid source to ensure the continuity and quality of energy in a locality with a stochastically changing population. The hybrid system is composed of a solar photovoltaic system, a wind turbine, and an energy storage system. The reliability of the system is evaluated based on the voltage level regulation on IEEE 33-bus and IEEE 69-bus standards. Power factor correction is performed, despite some reliability and robustness constraints. This work focuses on energy management in a hybrid system considering climatic disturbances on the one hand, and on the other hand, this work evaluates the energy quality and the cost of energy. A combination of genetic algorithms of particle swarm optimization (CGAPSO) shows high convergence speed, which illustrates the robustness of the proposed system. The study of this system shows its feasibility and compliance with standards. The results obtained show a significant reduction in the total cost of production of this proposed system.

Low Voltage Ride through Control Capability of a Large Grid Connected PV System Combining DC Chopper and Current Limiting Techniques

This paper presents the development and performance capability of a comprehensive Low voltage ride through (LVRT) control scheme that makes use of both the DC chopper and the current limiting based on the required reactive power during fault time. The study is conducted on an 8.5 MW single stage PV power plant (PVPP) connected to the Rwandan grid. In the event of fault disturbance, this control scheme helps to overcome the problems of excessive DC-link voltage by fast activation of the DC chopper operation. At the same instance, AC current is limited to the maximum rating of the inverter as a function of the injected reactive current. This helps overcome AC-over- current that may possibly lead to damage or disconnection of the inverter. The control scheme also ensures voltage support and power balance through the injection of reactive current as per grid code requirements. Selected simulations using MATLAB are carried out in the events of different kinds of fault caused voltage dips. Results demonstrate the effectiveness of the proposed LVRT control scheme.

Application of Slantlet Transform Based Support Vector Machine for Power Quality Detection and Classification

Concern towards power quality (PQ) has increased immensely due to the growing usage of high technology devices which are very sensitive towards voltage and current variations and the de-regulation of the electricity market. The impact of these voltage and current variations can lead to devices malfunction and production stoppages which lead to huge financial loss for the production company. The deregulation of electricity markets has made the industry become more competitive and distributed. Thus, a higher demand on reliability and quality of services will be required by the end customers. To ensure the power supply is at the highest quality, an automatic system for detection and localization of PQ activities in power system network is required. This paper proposed to use Slantlet Transform (SLT) with Support Vector Machine (SVM) to detect and localize several PQ disturbance, i.e. voltage sag, voltage swell, oscillatory-transient, odd-harmonics, interruption, voltage sag plus odd-harmonics, voltage swell plus odd-harmonics, voltage sag plus transient and pure sinewave signal were studied. The analysis on PQ disturbances signals was performed in two steps, which are extraction of feature disturbance and classification of the dis- turbance based on its type. To take on the characteristics of PQ signals, feature vector was constructed from the statistical value of the SLT signal coefficient and wavelets entropy at different nodes. The feature vectors of the PQ disturbances are then applied to SVM for the classification process. The result shows that the proposed method can detect and localize different type of single and multiple power quality signals. Finally, sensitivity of the proposed algorithm under noisy condition is investigated in this paper.

Simulations of the Performance of Maximum Power Point Tracking Algorithms Based on Experimental Data According to the Topologies of DC-DC Converters

Maximum Power Point Tracking (MPPT) algorithms are now widely used in PV systems independently of the weather conditions. In function of the application, a DC-DC converter topology is chosen without any previous performance test under normal weather conditions. This paper proposes an experimental evaluation of MPPT algorithms according to DC-DC converters topologies, under normal operation conditions. Four widely used MPPT algorithms i.e. Perturb and Observe (P & O), Hill Climbing (HC), Fixed step Increment of Conductance (INCF) and Variable step Increment of Conductance (INCV) are implemented using two topologies of DC-DC converters i.e. buck and boost converters. As input variables to the PV systems, recorded irradiance and temperature, and extracted photovoltaic parameters (ideality factor, series resistance and reverse saturation current) were used. The obtained results show that buck converter has a lot of power losses when controlled by each of the four MPPT algorithms. Meanwhile, boost converter presents a stable output power during the whole day. Once more, the results show that INCV algorithm has the best performance.

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.

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.

Development of High Torque and High Power Density Hybrid Excitation Flux Switching Motor for Traction Drive in Hybrid Electric Vehicles

This paper presents design feasibility study and development of a new hybrid excitation flux switching motor (HEFSM) as a contender for traction drives in hybrid electric vehicles (HEVs). Initially, the motor general construction, the basic working principle and the design concept of the proposed HEFSM are outlined. Then, the initial drive performances of the proposed HEFSM are evaluated based on 2D-FEA, in which the design restrictions, specifications and target performances are similar with conventional interior permanent magnet synchronous motor (IPMSM) used in HEV. Since the initial results fail to achieve the target performances, deterministic design optimization approach is used to treat several design parameters. After several cycles of optimization, the proposed motor makes it possible to obtain the target torque and power of 333 Nm and 123 kW, respectively. In addition, due to definite advantage of robust rotor structure of HEFSM, rotor mechanical stress prediction at maximum speed of 12,400 r/min is much lower than the mechanical stress in conventional IPMSM. Finally, the maximum torque and power density of the final design HEFSM are approximately 11.41 Nm/kg and 5.55 kW/kg, respectively, which is 19.98% and 58.12% more than the torque and power density in existing IPMSM for Lexus RX400h.

Modeling and Experimental Verification of Electric Vehicles Off-Grid Photovoltaic Powered Charging Station

With the increasing development of EVs, the energy demand from theconventional utility grid increases in proportion. On the other hand, photovoltaic(PV) energy sources can overcome several problems when charging EVs from theutility grid especially in remote areas. This paper presents an effective photovoltaic stand-alone charging station for EV applications. The proposed charging station incorporates PV array, a lithium-ion battery representing the EV battery, and alead-acid battery representing the energy storage system (ESS). A bidirectionalDC-DC converter is employed for charging/discharging the ESS and a unidirectional DC-DC converter is utilized for charging the EV battery. The proposed controllers achieve maximum power extraction from the PV and regulate the DC-linkvoltage. It also controls the voltage and current levels of both the ESS and the EVduring the charging/discharging process. The study has been applied to two caseswith different power levels. Analysis, simulation, and implementation of the proposed system are presented. A 120 W laboratory prototype is carried out to verifythe system performance, experimentally. Design guides for higher power levelsare proposed to help in choosing the proper parameters of the converters. Boththe simulation and experimental results are matched and verify the highperformance of the proposed system.

OFDM-based Low-voltage Powerline High Rate Communication

Based on the experimental results, a simplified model for low-voltage powerline used as a high frequency communication channel is presented. With this model, the Orthogonal Frequency Division Multiplexing (OFDM) based high rate digital communication over low-voltage powerline is analyzed and simulated. The capability of the signal transmission system in overcoming multi-path interference and selection of the system parameters are discussed. And time-domain simulation is carried out to investigate the transmission capability of the OFDM communication system for different mapping schemes and transmission power levels. Simulation results show that it is possible to realize high rate digital communication over low-voltage powerline using OFDM when the transmitted power is large enough.

Power Quality Issues Concerning Photovoltaic Generation and Electrical Vehicle Loads in Distribution Grids

The high utilization level of renewable generation including residential photovoltaic (PV) systems together with the uncontrolled charging of electric vehicles (EVs) can have a significant impact on load characteristics in distribution networks. Harmonic content of PV generation, EV charging loads, and their influence on power quality indicators in residential distribution networks are discussed in this paper. For investigating likely power quality scenarios, PV generation and EV charging measurement results including current harmonic amplitude and phase angle values are used and compared with present load characteristics. Different modelling scenarios are analysed and a simplified model of harmonics in PVs and EVs is offered. The results of the study show moderate additional harmonic distortion in residential load current and voltage distortion at the substation’s busbar when PV generation and EV loading are added. The scenarios presented in this paper can be further used for modelling the actual harmonic loads of the PVs and EVs in distribution networks.

Techno-Financial Analysis of Energy Access through Hybrid System with Solar PV under the Various Rural Community Models for State of Uttarakhand, India

Uttarakhand state comes under special category state where approximately 69.45% population lived in rural area under the population density with varied range of 37 to 607 persons per sq.km. Although Uttarakhand is having per capita consumption of 1112.29 kWh which is higher than national average per capita consumption of 779 kWh as till date, but remote communities, villages are not able to access clean, cheep and good quality of energy due to uneven terrain, lack of proper transmission & distribution lines [1]. 100% villages are electrified under the RGGVY scheme as per the Ministry of Power Government of India, but due to poor loading of transformer, lack of grid infrastructure and natural calamities, remote house owners are not able to get good quality of power thus affect the livelihood and source of income generation in various means [2]. As Uttarakhand state having future plans to be make state energy sufficient and energy access to all by year 2016-2017, so major ground level initiative have been taken by Government of Uttarakhand. The government of Uttarakhand has incorporated innovative business model to provide good quality of power with non-conventional energy source. Under the initiative invlovement of local people and village level, panchayats have ownership and responsibility to operate these clean energy business model to improve livelihood in remote hilly places of Uttarakhand. Under this analysis, five different type of community models are categorized as Community 1, Community 2, Community 3, Standalone 1 & Standalone 2 for rural &remote communities based on number of unclustered households with the distance covered between 200 m to 20 km, and electrical loads i.e. lighting, fan, mobile chargers, television along with time of day energy consumption patterns. These community models are for remote hilly location where grid integration and distribution lines are not feasible to built due to hilly terrain, low soil strength and huge expenses for expanding power cables for supplying good quality power. The preliminary studies and simulations has been done in HOMER tool by considering the various composite source of power, i.e. Solar PV with battery bank, Solar PV with battery Bank & Generator, and Solar PV along with DG. These three hybrid source of power generation with Solar PV as base source under five different community models, the techno-commercial feasibility has been analyzed in terms of load sharing proposition with Solar PV and battery, DG, Energy production through PV, load consumption per year, Excess and unmet energy monitoring, battery sizing to meet the load during nights, DG operation when the solar energy not available due to weather condition and non availability of sunshine in night. Financial feasibility has been examined in terms of levelized cost of energy, cost summary and O&M cost per year of three integrated sources of energy generation with Solar PV under each community model. Solar PV power plant , which is the best renewable source of energy to cater energy access issue in remote hilly places. The Uttarakhand receives good amout of daily average radiation level of 5.14 - 5.50 kWh/m2/day. Financial feasible community models for different hilly region based on their energy consumption need to be implemented with the help of local community by providing ownership to local people, panchayat, for it not only caters energy access issue but also provides clean, cheep, uninterruptable energy and improves livelihood standard to locals by engaging them into operation maintenance and tariff or rent collection. The study shows that Solar PV power plant with battery bank is the optimal solution considering life cycle cost of hybrid system. It is feasible due to low operation and maintenance cost, price declination of battery and Solar PV module, battery prices at time of replacement.

Microcontroller Control of Reactive Power Compensation for Growing Industrial Loads

Many industrial installations in developing countries start-up as small factories, without regard for the need of compensation of reactive power, leading to significant financial losses in the long term. By improving the power factor, the customer can reduce its power demand and potentially increase efficiency of their equipment. A PIC microcontroller is used to switch capacitor banks to compensate for the reactive power. In order to determine the size of the capacitor bank needed, the microcontroller calculates the phase difference between the voltage and the current. The results obtained based on the lagging power factor for three test loads show an improvement in the power factor from 0.52 to 0.96 under different test load conditions.

Modelling and Simulation of Performance of the Microgrid Frequency Stability Control during Unplanned Islanding: The Case Study of Mwenga Hydropower

A grid connected microgrid connects to the grid at a point of common coupling. Due to the great inertia of the grid which accelerates and decelerates the generator when its frequency tends to deviate, the grid connected microgrid operates at a frequency of the infinity bus. Frequency instability is one of the major challenges facing the grid connected microgrid during islanding. The power demand variation causes the variation in rotor speed, resulting to frequency deviation. Frequency can be brought back to standard by varying the power generation to match with the varying load. The performance of the frequency stability control system at Mwenga hydroelectric microgrid has been studied. Through site visitation, the power demand and generation status data were collected and analysed for model preparation. The results of the study indicate that, during islanding, the Mwenga rural electrification project is observed to be subjected to power imbalance which leads to frequency instability. Although the frequency control system tries to keep the system at a nominal frequency by maintaining the continuous balance between generation and varying load demand, however the system still operates with large magnitude of overshoot, undershoot and longer settling time.

Validation of Full-Converter Wind Power Plant Generic Model Based on Actual Fault Ride-Through Measurements

Modeling and validation of full power converter wind turbine models with field measurement data are rarely reported in papers. In this paper an aggregated generic dynamic model of the wind farm consisting of full power converter wind turbines is composed and the model validation based on actual field measurements is performed. The paper is based on the measurements obtained from the real short circuit test applied to connection point of observed wind farm. The presented approach for validating the composed model and fault ride-through （FRT） capability for the whole wind park is unique in overall practice and its significance and importance is described and analyzed.

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.