ORCID Profile
0000-0002-0975-0241
Current Organisations
Aalborg University
,
Aalborg Universitet
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Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2022
Publisher: Institution of Engineering and Technology (IET)
Date: 25-02-2019
Publisher: Elsevier BV
Date: 07-2020
Publisher: MDPI AG
Date: 29-11-2019
DOI: 10.3390/APP9235200
Abstract: Dynamic state estimation (DSE) for generators plays an important role in power system monitoring and control. Phasor measurement unit (PMU) has been widely utilized in DSE since it can acquire real-time synchronous data with high s ling frequency. However, random noise is unavoidable in PMU data, which cannot be directly used as the reference data for power grid dispatching and control. Therefore, the data measured by PMU need to be processed. In this paper, an adaptive ensemble square root Kalman filter (AEnSRF) is proposed, in which the ensemble square root filter (EnSRF) and Sage–Husa algorithm are utilized to estimate measurement noise online. Simulation results obtained by applying the proposed method show that the estimation accuracy of AEnSRF is better than that of ensemble Kalman filter (EnKF), and AEnSRF can track the measurement noise when the measurement noise changes.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Elsevier BV
Date: 12-2016
Publisher: MDPI AG
Date: 09-2020
DOI: 10.3390/EN13174522
Abstract: In the process of the operation and maintenance of secondary devices in smart substation, a wealth of defect texts containing the state information of the equipment is generated. Aiming to overcome the low efficiency and low accuracy problems of artificial power text classification and mining, combined with the characteristics of power equipment defect texts, a defect texts mining method for a secondary device in a smart substation is proposed, which integrates global vectors for word representation (GloVe) method and attention-based bidirectional long short-term memory (BiLSTM-Attention) method in one model. First, the characteristics of the defect texts are analyzed and preprocessed to improve the quality of the defect texts. Then, defect texts are segmented into words, and the words are mapped to the high-dimensional feature space based on the global vectors for word representation (GloVe) model to form distributed word vectors. Finally, a text classification model based on BiLSTM-Attention was proposed to classify the defect texts of a secondary device. Precision, Recall and F1-score are selected as evaluation indicators, and compared with traditional machine learning and deep learning models. The analysis of a case study shows that the BiLSTM-Attention model has better performance and can achieve the intelligent, accurate and efficient classification of secondary device defect texts. It can assist the operation and maintenance personnel to make scientific maintenance decisions on a secondary device and improve the level of intelligent management of equipment.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2018
Publisher: MDPI AG
Date: 15-06-2021
DOI: 10.3390/EN14123548
Abstract: In this article, an efficient long-term novel scheduling technique is proposed for allocating capacitors in a combined system involving distributed generation (DG) along with radial distribution systems (RDS). We introduce a unique multi-objective function that focuses on the reduction of power loss with the maximization of voltage stability index (VSI) subjected to constraints of equality and inequality systems. Loss sensitivity factor and VSI together are involved in pre-identifying the locations of capacitors and DG. Determination of the optimal size of capacitor and DG is performed by utilizing the Bat algorithm (BA) for all the loads in RDS. The conventional approach considers the medium load of (1.0) condition generally, but the proposed method changes the feeder loads linearly, ranging from light load (0.5) to peak load (1.6) with the value of step size as 1%. BA determines the optimal size of the capacitor and DG for each step load. The curve fitting technique is used for deducing the generalized equation of capacitor size and DG for all conditions of the load with the various loading condition sized by distributed network operators (DNOs). Further, various load models such as industrial, residential, and commercial loads have been considered to show the efficiency of the present approach. Validation of results is performed in different scenarios on a 69-bus test system and on a standard IEEE 33-bus system. The results exhibit improved accuracy with less power loss value, superior bus voltage, and stability of system voltage with a higher rate of convergence.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: IEEE
Date: 04-08-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2020
Publisher: Elsevier BV
Date: 02-2015
Publisher: Elsevier BV
Date: 05-2016
Publisher: MDPI AG
Date: 02-03-2020
DOI: 10.3390/EN13051120
Abstract: The rapid growth of grid integrated renewable energy (RE) sources resulted in development of the hybrid grids. Variable nature of RE generation resulted in problems related to the power quality (PQ), power system reliability, and adversely affects the protection relay operation. High penetration of RE to the utility grid is achieved using multi-tapped lines for integrating the wind and solar energy and also to supply loads. This created considerable challenges for power system protection. To overcome these challenges, an algorithm is introduced in this paper for providing protection to the hybrid grid with high RE penetration level. All types of fault were identified using a fault index (FI), which is based on both the voltage and current features. This FI is computed using element to element multiplication of current-based Wigner distribution index (WD-index) and voltage-based alienation index (ALN-index). Application of the algorithm is generalized by testing the algorithm for the recognition of faults during different scenarios such as fault at different locations on hybrid grid, different fault incident angles, fault impedances, s ling frequency, hybrid line consisting of overhead (OH) line and underground (UG) cable sections, and presence of noise. The algorithm is successfully tested for discriminating the switching events from the faulty events. Faults were classified using the number of faulty phases recognized using FI. A ground fault index (GFI) computed using the zero sequence current-based WD-index is also introduced for differentiating double phase and double phase to ground faults. The algorithm is validated using IEEE-13 nodes test network modelled as hybrid grid by integrating wind and solar energy plants. Performance of algorithm is effectively established by comparing with the discrete wavelet transform (DWT) and Stockwell transform based protection schemes.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2020
Publisher: Elsevier BV
Date: 09-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2022
Publisher: MDPI AG
Date: 18-06-2020
DOI: 10.3390/APP10124200
Abstract: In recent years, the importance of online monitoring short-term voltage stability has been considerably increased. Unstable cases due to response of fast dynamic loads such as induction motors to the serious disturbances can be avoided by online monitoring of voltage transients and activating fast and appropriate controls to encounter deep and prolonged voltage drop. In this paper, a set of indices based on the phasor measurement unit (PMU) measurements are introduced and compared for short-term voltage stability. To increase efficiency of the indices, a special algorithm for each index is proposed by using the investigation of the results of applying them to six disturbances’ scenarios simulated on the IEEE 39 bus system. The disturbance scenarios are representative of different cases of stable, unstable, and deep and prolonged voltage drop associated with short-term voltage transients. The performance of these indices are studied in terms of the time and accuracy required for determining the short-term voltage stability/instability cases. It is shown that the proposed method has better performance in comparison with other techniques that can be applied to power systems in reality.
Publisher: Elsevier BV
Date: 06-2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: MDPI AG
Date: 29-10-2020
DOI: 10.3390/SU12218991
Abstract: The remarkable growth of distributed generation (DG) penetration inside electrical power systems turns the familiar passive distribution networks (PDNs) into active distribution networks (ADNs). Based on the backward/forward sweep method (BFS), a new power-flow algorithm was developed in this paper. The algorithm is flexible to handle the bidirectional flow of power that characterizes the modern ADNs. Models of the commonly used distribution network components were integrated with the developed algorithm to form a comprehensive tool. This tool is valid for modeling either balanced or unbalanced ADNs with an unlimited number of nodes or laterals. The integrated models involve modeling of distribution lines, losses inside distribution transformers, automatic voltage regulators (AVRs), DG units, shunt capacitor banks (SCBs) and different load models. To verify its validity, the presented algorithm was first applied to the unbalanced IEEE 37-node standard feeder in both passive and active states. Moreover, the algorithm was then applied to a balanced 22 kV real distribution network as a case study. The selected network is located in a remote area in the western desert of Upper Egypt, far away from the Egyptian unified national grid. Accordingly, the paper examines the current and future situation of the Egyptian electricity market. Comparison studies between the performance of the proposed ADNs and the classical PDNs are discussed. Simulation results are presented to demonstrate the effectiveness of the proposed ADNs in preserving the network assets, improving the system performance and minimizing the power losses.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: SAGE Publications
Date: 07-05-2018
Abstract: Globally, education policy reforms are increasingly aimed at attending to excellence in education. This is mainly expressed as attempts at raising educational standards generally, but also of identifying intellectual elites and making special provisions for them. Denmark, which is otherwise considered an exponent of an equality-oriented tradition in education, is now pursuing strategies of developing talent throughout the educational system, which is to cater more to the needs of so-called gifted and talented students. This policy is claimed to have found inspiration from Australia, where some of the states have been pursuing such policies for several years and where we find a more developed tradition for this. The paper is focused on understanding what concept of excellence such education policies imply we aim to analyse the targeted groups with respect to means of identification and development, and to analyse the wider implications of such policies. The analysis is empirically focused on education policy documents on gifted and talented educational provisions at national/state level. Beginning with the political discourse of talent development in education as it has appeared in Denmark, we analyse this in relation to the policies and curricular provisions for the gifted and talented in England and Australia.
Publisher: MDPI AG
Date: 21-09-2021
DOI: 10.3390/EN14185983
Abstract: In recent decades, various types of control techniques have been proposed for use in power systems. Among them, the use of a proportional–integral–derivative (PID) controller is widely recognized as an effective technique. The generalized type of this controller is the fractional-order PID (FOPID) controller. This type of controller provides a wider range of stability area due to the fractional orders of integrals and derivatives. These types of controllers have been significantly considered as a new approach in power engineering that can enhance the operation and stability of power systems. This paper represents a comprehensive overview of the FOPID controller and its applications in modern power systems for enhancing low-frequency oscillation (LFO) d ing. In addition, the performance of this type of controller has been evaluated in a benchmark test system. It can be a driver for the development of FOPID controller applications in modern power systems. Investigation of different pieces of research shows that FOPID controllers, as robust controllers, can play an efficient role in modern power systems.
Publisher: Elsevier BV
Date: 05-2016
Publisher: MDPI AG
Date: 22-11-2020
DOI: 10.3390/APP10228283
Abstract: The Frequency Response Analysis approach (FRA) is useful in the fault diagnosis of transformers. However, its usefulness in diagnosing any potential sources of Partial Discharge (PD) in transformers has not been thoroughly investigated so far. In this work, the use of Impulse voltage-based FRA (IFRA) in diagnosing inter-turn shorts and potential sources of PD were investigated on a 315 kVA, 11 kV/433 V transformer. Inter-turn shorts and PD sources were emulated and the usefulness of IFRA in their diagnosis was investigated while using switching impulse voltage at different magnitude levels as the test signals. For emulating the inter-turn shorts and the PDs, special tappings were provided on one of the 11 kV windings through the low capacitance bushings. Low voltage impulse was successful in diagnosing the inter-turn shorts, but unsuccessful in identifying the sources of PDs. During the test condition, the test voltage was adjusted with the presence of artificially created PD sources. The frequency response of the transformer before and after the inception of PD was observed and analyzed in this article. The FRA results demonstrated that the switching impulse voltage based IFRA approach at moderate voltages could be useful in diagnosing the presence of the potential sources of PDs.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2022
Publisher: Hindawi Limited
Date: 21-08-2021
Publisher: MDPI AG
Date: 30-12-2020
DOI: 10.3390/APP11010274
Abstract: The electrical demands in several countries around the world are increasing due to the huge energy requirements of prosperous economies and the human activities of modern life [...]
Publisher: MDPI AG
Date: 08-2020
DOI: 10.3390/EN13153960
Abstract: A new non-isolated modified SEPIC front-end dc-dc converter for the low power system is proposed in this paper, and this converter is the next level of the traditional SEPIC converter with additional devices, such as two diodes and splitting of the output capacitor into two equal parts. The circuit topology proposed in this paper is formulated by combining the boost structure with the traditional SEPIC converter. Therefore, the proposed converter has the benefit of the SEPIC converter, such as continuous input current. The proposed circuit structure also improves the features, such as high voltage gain and high conversion efficiency. The converter comprises one MOSFET switch, one coupled inductor, three diodes, and two capacitors, including the output capacitor. The converter effectively recovers the leakage energy of the coupled inductor through the passive cl circuit. The operation of the proposed converter is explained in continuous conduction mode (CCM) and discontinuous conduction mode (DCM). The required voltage gain of the converter can be acquired by adjusting the coupled inductor turn’s ratio along with the additional devices at less duty cycle of the switch. The simulation of the proposed converter under CCM is carried out, and an experimental prototype of 100 W, 25 V/200 V is made, and the experimental outcomes are presented to validate the theoretical discussions of the proposed converter. The operating performance of the proposed converter is compared with the converters discussed in the literature. The proposed converter can be extended by connecting voltage multiplier (VM) cell circuits to get the ultra-high voltage gain.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institution of Engineering and Technology (IET)
Date: 12-2017
Publisher: MDPI AG
Date: 16-09-2021
DOI: 10.3390/SMARTCITIES4030063
Abstract: One of the important aspects of realizing smart cities is developing smart homes/buildings and, from the energy perspective, designing and implementing an efficient smart home area energy management system (HAEMS) is vital. To be effective, the HAEMS should include various electrical appliances as well as local distributed/renewable energy resources and energy storage systems, with the whole system as a microgrid. However, the collecting and processing of the data associated with these appliances/resources are challenging in terms of the required sensors/communication infrastructure and computational burden. Thanks to the internet-of-things and cloud computing technologies, the physical requirements for handling the data have been provided however, they demand suitable optimization/management schemes. In this article, a HAEMS is developed using cloud services to increase the accuracy and speed of the data processing. A management protocol is proposed that provides an optimal schedule for a day-ahead operation of the electrical equipment of smart residential homes under welfare indicators. The proposed system comprises three layers: (1) sensors associated with the home appliances and generation/storage units, (2) local fog nodes, and (3) a cloud where the information is processed bilaterally with HAEMS and the hourly optimal operation of appliances/generation/storage units is planned. The neural network and genetic algorithm (GA) are used as part of the HAEMS program. The neural network is used to predict the amount of workload corresponding to users’ requests. Improving the load factor and the economic efficiency are considered as the objective function that is optimized using GA. Numerical studies are performed in the MATLAB platform and the results are compared with a conventional method.
Publisher: MDPI AG
Date: 23-06-2022
DOI: 10.3390/INVENTIONS7030048
Abstract: Advances in technology and population growth are two factors responsible for increasing electricity consumption, which directly increases the production of electrical energy. Additionally, due to environmental, technical and economic constraints, it is challenging to meet demand at certain hours, such as peak hours. Therefore, it is necessary to manage network consumption to modify the peak load and tackle power system constraints. One way to achieve this goal is to use a demand response program. The home energy management system (HEMS), based on advanced internet of things (IoT) technology, has attracted the special attention of engineers in the smart grid (SG) field and has the tasks of demand-side management (DSM) and helping to control equality between demand and electricity supply. The main performance of the HEMS is based on the optimal scheduling of home appliances because it manages power consumption by automatically controlling loads and transferring them from peak hours to off-peak hours. This paper presents a multi-objective version of a newly introduced metaheuristic called the bald eagle search optimization algorithm (BESOA) to discover the optimal scheduling of home appliances. Furthermore, the HEMS architecture is programmed based on MATLAB and ThingSpeak modules. The HEMS uses the BESOA algorithm to find the optimal schedule pattern to reduce daily electricity costs, reduce the PAR, and increase user comfort. The results show the suggested system’s ability to obtain optimal home energy management, decreasing the energy cost, microgrid emission cost, and PAR (peak to average ratio).
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Institution of Engineering and Technology (IET)
Date: 03-2009
Publisher: MDPI AG
Date: 28-02-2021
DOI: 10.3390/EN14051317
Abstract: The need for regulating the operation of unhealthy motor drives has motivated the researchers to modify the control techniques in order to be valid for the new drive state. The use of a fault-tolerant facility is an attractive feature of multiphase machines therefore, the applicability of different controllers has been established for the operation under open-phase fault conditions. The considered control algorithms were utilized to analyze the operation of the unhealthy system and evaluating the capability of the control to regulate the speed and torque under the fault condition. However, the majority of these studies considered only one control algorithm to be tested with the faulty system without comparing its performance with other techniques. The performance comparison is a vital way to visualize the features and characteristics of each algorithm. For this purpose, this paper deals with the performance comparison of the hysteresis controller, RFOC based on resonant controller and direct torque control (DTC) control under open-circuit fault conditions. A detailed comparison between the three control techniques is presented to outline the main differences between the three control procedures and identify the most appropriate technique in between.
Publisher: IEEE
Date: 06-2019
Publisher: MDPI AG
Date: 09-03-2019
DOI: 10.3390/APP9050990
Abstract: In the event of a generator loss or disturbance, the power system frequency declines quickly and overall system stability is at risk. During these scenarios, under frequency load shedding is triggered to restore the power system frequency. The main stage of modern adaptive under frequency load shedding techniques is disturbance estimation. However, the swing equation is widely used in disturbance estimation but has some critical estimation errors. In this paper, instead of using the swing equation we proposed the use of a disturbance observer to estimate the curtailed power. By making use of wide area measurements, a system frequency response model, which is a representative of the whole power system, can be realized in real time. Using different power system states of the developed model, a disturbance observer can be designed as well. The main advantage of the disturbance observer is that it can accurately estimate the disturbance magnitude and its location in a very short time. Further investigations show that by using the disturbance observer disturbances, which occur at the same time or at different times in different areas regardless of the magnitude or size, accurate estimations can be made. To ascertain the efficiency of the proposed scheme, simulations are done for a four-area power system using Matlab/Simulink.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2020
Publisher: MDPI AG
Date: 19-02-2021
DOI: 10.3390/ELECTRONICS10040492
Abstract: The integration of wind energy systems (WECS) into the power grid through power electronic converters should ensure the high performance of the control system. In spite of several advantages of conventional Finite control set-model predictive controller (FCS-MPC), variable switching frequency and high computational burden are considered its main drawbacks. In this paper, a fast FCS-MPC of a machine side converter (MSC) of direct-driven permanent magnet synchronous generator (PMSG) based wind turbines for wind energy conversion system is proposed. The wind energy conversion system has been realized using a direct driven PMSG and a full-scale back-to-back power converter. The proposed controller is designed to reduce the required calculations in each horizon. In addition, the performance of conventional FCS-MPC is compared with the proposed method, and an improvement in total harmonic distortion spectra and simulation time required even when imposing a lower s ling frequency was found. To overcome the variable switching frequency problem, a modulation algorithm is introduced in the minimization process of modulated FCS-MPC. To keep the proposed system attached to the utility during a fault, a coordinated pitch angle control and low voltage-ride through (LVRT) algorithm is designed and inserted in the vector control of the grid side converter (GSC) to supply reactive power to the grid during fault for ensuring safe operation of the inverter and meeting the grid code requirements. The effectiveness of the proposed controller is illustrated using simulation results under different operating conditions.
Publisher: IEEE
Date: 05-2016
Publisher: IEEE
Date: 09-2019
Publisher: MDPI AG
Date: 11-11-2020
DOI: 10.3390/APP10227985
Abstract: The complexity of power system networks is increasing continuously due to the addition of high capacity transmission lines. Faults on these lines may deteriorate the power flow pattern in the network. This can be avoided by the use of effective protection schemes. This paper presents an algorithm for detecting and classifying faults on the transmission network. Fault detection is achieved by utilizing the fault index, which depends on a combination of characteristics extracted from the current signal by the application of the Stockwell transform and Wigner distribution function (WDF). Various faults are categorized using the quantity of phases with a faulty nature. The fault events like phase to-ground (L-G), two phases (LL), two phases to-ground (LL-G), and three phases to-ground (LLL-G) are investigated in this study. The performance of the algorithm designed for the protection scheme is tested for the variations in the impedance during the fault event, variations in the angle of the fault incidence, different fault locations, the condition of the power flow in the reverse direction, the availability of noise, and the fault on the hybrid line consisting of two sections of underground cable and the overhead line. The algorithm is also analyzed for discriminating switching incidents from fault cases. A comparative study is used to establish the superiority of the proposed technique as compared to the Wavelet transform (WT) based protection scheme. The performance of the protection technique is established in MATLAB/Simulink software using a test network of the transmission line with two terminals.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: IEEE
Date: 09-2018
Publisher: MDPI AG
Date: 10-05-2020
DOI: 10.3390/EN13092383
Abstract: Penetration level of renewable energy (RE) in the utility grid is continuously increasing to minimize the environmental concerns, risk of energy security, and depletion of fossil fuels. The uncertain nature and availability of RE power for a short duration have created problems related to the protection, grid security, power reliability, and power quality. Further, integration of RE sources near the load centers has also pronounced the protection issues, such as false tripping, delayed tripping, etc. Hence, this paper introduces a hybrid grid protection scheme (HGPS) for the protection of the grid with RE integration. This combines the merits of the Stockwell Transform, Hilbert Transform, and Alienation Coefficient to improve performance of the protection scheme. The Stockwell Transform-based Median and Summation Index (SMSI) utilizing current signals, Hilbert Transform-based derivative index (HDI) utilizing voltage signals, and Alienation Coefficient index (ACI) utilizing voltage signals were used to compute a proposed Stockwell Transform-, Hilbert Transform-, and Alienation-based fault index (SAHFI). This SAHFI was used to recognize the fault conditions. The fault conditions were categorized using the number of faulty phases and the proposed Stockwell Transform and Hilbert Transform-based ground fault index (SHGFI) utilizing zero sequence currents. The fault conditions, such as phase and ground (PGF), any two phases (TPF), any two phases and ground (TPGF), all three phases (ATPF), and all three phases and ground (ATPGF), were recognized effectively, using the proposed SAHFI. The proposed method has the following merits: performance is least affected by the noise, it is effective in recognizing fault conditions in minimum time, and it is also effective in recognizing the fault conditions in different scenarios of the grid. Performance of the proposed approach was found to be superior compared to the discrete wavelet transform (DWT)-based method reported in the literature. The study was performed using the hybrid grid test system realized by integrating wind and solar photovoltaic (PV) plants to the IEEE-13 nodes network in MATLAB software.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2021
Publisher: MDPI AG
Date: 19-02-2020
DOI: 10.3390/APP10041384
Abstract: In this paper, an improved hybridization of an evolutionary algorithm, named permutated oppositional differential evolution sine cosine algorithm (PODESCA) and also a sensitivity-based decision-making technique (SBDMT) are proposed to tackle the optimal planning of shunt capacitors (OPSC) problem in different-scale radial distribution systems (RDSs). The evolved PODESCA uniquely utilizes the mechanisms of differential evolution (DE) and an enhanced sine–cosine algorithm (SCA) to constitute the algorithm’s main structure. In addition, quasi-oppositional technique (QOT) is applied at the initialization stage to generate the initial population, and also inside the main loop. PODESCA is implemented to solve the OPSC problem, where the objective is to minimize the system’s total cost with the presence of capacitors subject to different operational constraints. Moreover, SBDMT is developed by using a multi-criteria decision-making (MCDM) approach namely the technique for the order of preference by similarity to ideal solution (TOPSIS). By applying this approach, four sensitivity-based indices (SBIs) are set as inputs of TOPSIS, whereas the output is the highest potential buses for SC placement. Consequently, the OPSC problem’s search space is extensively and effectively reduced. Hence, based on the reduced search space, PODESCA is reimplemented on the OPSC problem, and the obtained results with and without reducing the search space by the proposed SBDMT are then compared. For further validation of the proposed methods, three RDSs are used, and then the results are compared with different methods from the literature. The performed comparisons demonstrate that the proposed methods overcome several previous methods and they are recommended as effective and robust techniques for solving the OPSC problem.
Publisher: SAGE Publications
Date: 18-05-2020
Abstract: This paper presents the application of information gap decision theory (IGDT) to deal with uncertainties associated with load forecasting in dynamic, environment constrained, coordinated generation and transmission expansion planning. Traditionally, the gaseous emissions are constrained over the whole system. Conventional methods cannot guarantee a practical expansion plan since huge emissions can still occur on some buses in the power system. This paper introduces a per-bus emission limit to avoid extreme emissions in highly populated areas. The effect of nodal emission limits is fully discussed and compared to a conventional method. The model is kept linear using the big M approach to decrease the model computational burden. Reliability is considered by limiting the estimated load not served in each year over the planning horizon. The cost of fuel transportation and fuel limits are considered in order to make the model more realistic and practical. The effectiveness of the proposed model is verified by implementation on Garver 6 bus, IEEE 30 bus, and 118 bus test systems.
Publisher: Elsevier BV
Date: 02-2018
Publisher: IEEE
Date: 06-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2021
Publisher: MDPI AG
Date: 16-11-2021
DOI: 10.3390/ELECTRONICS10222814
Abstract: In this paper, a new modulated finite control set-model predictive control (FCS-MPC) methodology is proposed for a quasi-Z-source inverter (qZSI). The application of the qZSI in this paper is to drive the permanent magnet synchronous machine (PMSM). The proposed methodology calculates the optimal duration time (ODT) for the candidate vector from the switching patterns of the inverter after it is selected from the FCS-MPC algorithm. The control objective of the FCS-MPC are the three-phase currents of PMSM, when the motor speed is below or equal to the base speed. While at a speed beyond the based speed, the inductor current and capacitor voltage of the qZS network are added as control objectives. For each candidate optimal vector, the optimal time, which is a part of the s ling interval, is determined based on minimizing the ripples of the control objectives using a quadratic cost function. Then, the optimal vector is applied only to the inverter switches during the calculated ODT at the start of the s ling interval, while the zero vector is applied during the remaining part of the s ling interval. To reduce the calculation burden, the zero-state is excluded from the possible states of the inverter, and the sub-cost function definition is used for the inductor current regulation. The proposed modulated FCS-MPC is compared with the unmodulated FCS-MPC at the same parameters to handle a fair comparison. The simulation results based on the MATLAB/Simulink© software shows the superiority of the proposed algorithm compared to the unmodulated FCS-MPC in terms of a lower ripple in the inductor current and capacitor voltage, and a lower THD for the PMSM currents.
Publisher: MDPI AG
Date: 20-09-2018
DOI: 10.3390/EN11102497
Abstract: Power systems are the most complex systems that have been created by men in history. To operate such systems in a stable mode, several control loops are needed. Voltage frequency plays a vital role in power systems which need to be properly controlled. To this end, primary and secondary frequency control loops are used to control the frequency of the voltage in power systems. Secondary frequency control, which is called Load Frequency Control (LFC), is responsible for maintaining the frequency in a desirable level after a disturbance. Likewise, the power exchanges between different control areas are controlled by LFC approaches. In recent decades, many control approaches have been suggested for LFC in power systems. This paper presents a comprehensive literature survey on the topic of LFC. In this survey, the used LFC models for erse configurations of power systems are firstly investigated and classified for both conventional and future smart power systems. Furthermore, the proposed control strategies for LFC are studied and categorized into different control groups. The paper concludes with highlighting the research gaps and presenting some new research directions in the field of LFC.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: MDPI AG
Date: 18-09-2021
DOI: 10.3390/FI13090239
Abstract: Hindi is the official language of India and used by a large population for several public services like postal, bank, judiciary, and public surveys. Efficient management of these services needs language-based automation. The proposed model addresses the problem of handwritten Hindi character recognition using a machine learning approach. The pre-trained DCNN models namely InceptionV3-Net, VGG19-Net, and ResNet50 were used for the extraction of salient features from the characters’ images. A novel approach of fusion is adopted in the proposed work the DCNN-based features are fused with the handcrafted features received from Bi-orthogonal discrete wavelet transform. The feature size was reduced by the Principal Component Analysis method. The hybrid features were examined with popular classifiers namely Multi-Layer Perceptron (MLP) and Support Vector Machine (SVM). The recognition cost was reduced by 84.37%. The model achieved significant scores of precision, recall, and F1-measure—98.78%, 98.67%, and 98.69%—with overall recognition accuracy of 98.73%.
Publisher: Elsevier BV
Date: 03-2020
Publisher: Elsevier BV
Date: 06-2019
Publisher: MDPI AG
Date: 19-10-2018
DOI: 10.3390/EN11102819
Abstract: There has been a considerable importance for the islanding detection due to the growing integration of distributed generations (DGs) in the modern power grids. This paper proposes a novel active islanding detection scheme for synchronous DGs, considering two additional compensators and a positive feedback for each of active and reactive power control loops. The added blocks are designed using the small gain theorem and stability margins definition considering characteristics of open loop transfer functions of synchronous DG control loops. Islanding can be detected using the proposed method even where there is an exact match between generation and local load without sacrificing power quality. In addition, the performance of the proposed method can be retained even with high penetration of motor loads. The proposed scheme improves the stability and power quality of the grid, when the synchronous DG is subjected to the grid-connected disturbances. Furthermore, this method augments the stability margins of the system in the grid-connected conditions to enhance the disturbances ride-through capability of the system and reduce the negative impact of the active methods on the power quality. Simultaneous advantages of the proposed scheme are demonstrated by modeling a test system in MATLAB software and time-domain simulation achieved by PSCAD.
Publisher: MDPI AG
Date: 20-06-2021
DOI: 10.3390/APP11125706
Abstract: Cyber-physical threats as false data injection attacks (FDIAs) in islanded smart microgrids (ISMGs) are typical accretion attacks, which need urgent consideration. In this regard, this paper proposes a novel cyber-attack detection model to detect FDIAs based on singular value decomposition (SVD) and fast Fourier transform (FFT). Since new research are mostly focusing on FDIAs detection in DC systems, paying attention to AC systems attack detection is also necessary hence, AC state estimation (SE) have been used in SI analysis and in considering renewable energy sources effect. Whenever malicious data are added into the system state vectors, vectors’ temporal and spatial datum relations might drift from usual operating conditions. In this approach, switching surface based on sliding mode controllers is dialyzed to regulate detailed FFT’s coefficients to calculate singular values. Indexes are determined according to the composition of FFT and SVD in voltage/current switching surface to distinguish the potential cyber-attack. This protection layout is presented for cyber-attack detection and is studied in various types of FDIA forms like litude and vector derivation of signals, which exchanged between agents such as smart sensor, control units, smart loads, etc. The prominent advantage of the proposed detection layout is to reduce the time (less than 10 milliseconds from the attack outset) in several kinds of case studies. The proposed method can detect more than 96% accuracy from 2967 s le tests. The performances of the method are carried out on AC-ISMG in MATLAB/Simulink environment.
Publisher: MDPI AG
Date: 28-09-2020
DOI: 10.3390/APP10196792
Abstract: Nowadays, the application of distributed energy sources (DES) has been extensively employed to serve the power system by supplying the power into the grid and improving the power quality (PQ). Therefore, DES is one solution that can efficiently overcome the energy crisis and climate change problems. The DES, such as solar photovoltaic (PV), wind turbine (WT), and battery energy storage systems (BESS), are incorporated to form the microgrid (MG), which are interfaced with the power system. However, interfacing MG to the power system is undoubtedly a big challenge. Therefore, more focus is required on the control strategy to control the MG with the power system. To address the PQ problems, a controlled MG integrated with a hybrid shunt active power filter (HSAPF) is provided in this work. For controlling the MG integrated HSAPF, different control strategies are applied. In this work, a learning-based incremental conductance (LINC) technique is used as a maximum power point tracking (MPPT) for tracking the maximum power in PV and WT. The voltage source inverter (VSI) of HSAPF is controlled using a wavelet-based technique with a synchronous reference frame (SRF). The main focus is to improve the PQ by compensating the harmonics and regulating the reactive power in both grid-interactive and islanded condition and also supply continuous and adequate power to the non-linear load. The power system model has been developed with MATLAB/Simulink tool, which shows the efficiency of the proposed method. The results obtained have been satisfactorily under various operating conditions and can be validated further using the real-time dSPACE.
Publisher: MDPI AG
Date: 02-2019
DOI: 10.3390/APP9030508
Abstract: Power systems that are known as the most complex systems encounter different types of disturbances and emergence events. To operate such systems in a stable mode, several control protection techniques are in need. Frequency plays a vital role in power systems and needs to be properly maintained in a permissible level. To this end, under-frequency load-shedding (UFLS) techniques are used to intercept the frequency decline when a system encounters a severe disturbance. In this paper, a novel, wide-area measurement system (WAMS)-based optimal UFLS technique is proposed. The system frequency response (SFR) model is identified online based on the real-time measurements collected by phasor measurement units (PMUs). Then, the SFR model is used to design a new optimal multi-stage UFLS scheme. Imperialist competitive algorithm (ICA), which is a powerful evolutionary computing method, is then adopted for solving the suggested multi-stage UFLS optimization problem. The applicability of the proposed method is shown on a practical test system. The effectiveness of the proposed optimal multi-stage UFLS scheme is verified by several simulation and comparison scenarios.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: MDPI AG
Date: 15-10-2021
DOI: 10.3390/EN14206684
Abstract: Each country must determine the Grid Code conditions and apply these criteria to integrate distributed generation (DG) systems into the existing electricity grid and to ensure a stable power system. Thus, experimental studies are required to provide an effective, national, and specific Grid Code. In this study, the Turkish Grid Code’s electrical criteria were examined, and the application of these criteria was carried out on a developed PV-based DG. A real-time energy management system (RTEMS) was proposed in the study. Electrical parameters on the developed DG were monitored in real-time by considering IEEE 1547, IEEE 929–2000, and Turkey’s electrical criteria. A practical grid code study was firstly investigated in detail about the Turkish Grid Code by a developed real-time monitoring-control and protection system. The proposed RTEMS method in the study is implemented as an inverter-resident system thus, it provides advantages over many energy management systems embedded in the inverter. The degradation in power quality and non-detection zone (NDZ) problems encountered in active and passive island mode detection methods developed embedded in the inverter are eliminated in the proposed method. With the RTEMS method, where under and over-voltage, under and over voltage frequency, and unintentional island mode events can be detected in real-time, both the existing grid-code requirements are met, and the existing power quality and NDZ problem is eliminated with the recommended inverter-independent RTEMS method.
Publisher: MDPI AG
Date: 19-04-2021
DOI: 10.3390/APP11083661
Abstract: Today, in various leading power utilities in developing countries, achieving optimal operational energy management and planning, taking into account the costs reduction of generation, transmission and distribution of electricity, and also reducing the emission of an environmental pollutant becomes more and more important. Optimal use of renewable energy sources (RESs) is an effective way to achieve these goals. In this regard, in this research article, an improved multi-objective differential evolutionary (IMODE) optimization algorithm is suggested and performed to dispatch electricity generations in a smart microgrid (MG) system, taking into account economy and emission as competitive issues. In this paper, a nonlinear equation of multi-objective optimization issue with various equality and inequality limitations is formulated in order to lower the total operational costs of the MG considering environmental pollution effects simultaneously. In order to address the issue of optimal operation of the MG in single-objective and multi-objective forms, an intelligent method according to the improved differential evolutionary (IDE) optimization is utilized and performed and the proposed algorithm is implemented on different problems. First, it is assumed that there is no limit to the exchange of power overhead, and secondly, the limitation of power exchange with the upstream grid is considered. In multi-objective mode, these two modes are also considered. In order to show the impact of renewable energy on the cost, in the third part of the simulations, the operation is solved with maximum participation of renewable energy sources. In the final section, the sensitivity analysis on the number of populations in this problem is performed. The obtained results of the simulation are compared to differential evolutionary (DE) and particle swarm optimization (PSO) techniques. The effectiveness of the suggested multi-operational energy management method is confirmed by applying a study case system.
Publisher: MDPI AG
Date: 16-08-2019
DOI: 10.3390/EN12163160
Abstract: Different issues will be raised and highlighted by emerging distributed generations (DGs) into modern power systems in which the islanding detection is the most important. In the islanding situation, a part of the system which consists of at least one DG, passive grid, and local load, becomes fully separated from the main grid. Several detection methods of islanding have been proposed in recent researches based on measured electrical parameters of the system. However, islanding detection based on local measurements suffers from the non-detection zone (NDZ) and undesirable detection during grid-connected events. This paper proposes a passive islanding detection algorithm for all types of DGs by appropriate combining the measured frequency, voltage, current, and phase angle and their rate of changes at the point of common coupling (PCC). The proposed algorithm detects the islanding situation, even with the exact zero power mismatches. Proposed algorithm discriminates between the islanding situation and non-islanding disturbances, such as short circuit faults, capacitor faults, and load switching in a proper time and without mal-operation. In addition, the performance of the proposed algorithm has been evaluated under different scenarios by performing the algorithm on the IEEE 13-bus distribution system.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Elsevier BV
Date: 04-2018
Publisher: MDPI AG
Date: 03-04-2020
DOI: 10.3390/EN13071706
Abstract: The energy management system is executed in microgrids for optimal integration of distributed energy resources (DERs) into the power distribution grids. To this end, various strategies have been more focused on cost reduction, whereas effectively both economic and technical indices/factors have to be considered simultaneously. Therefore, in this paper, a two-layer optimization model is proposed to minimize the operation costs, voltage fluctuations, and power losses of smart microgrids. In the outer-layer, the size and capacity of DERs including renewable energy sources (RES), electric vehicles (EV) charging stations and energy storage systems (ESS), are obtained simultaneously. The inner-layer corresponds to the scheduled operation of EVs and ESSs using an integrated coordination model (ICM). The ICM is a fuzzy interface that has been adopted to address the multi-objectivity of the cost function developed based on hourly demand response, state of charges of EVs and ESS, and electricity price. Demand response is implemented in the ICM to investigate the effect of time-of-use electricity prices on optimal energy management. To solve the optimization problem and load-flow equations, hybrid genetic algorithm (GA)-particle swarm optimization (PSO) and backward-forward sweep algorithms are deployed, respectively. One-day simulation results confirm that the proposed model can reduce the power loss, voltage fluctuations and electricity supply cost by 51%, 40.77%, and 55.21%, respectively, which can considerably improve power system stability and energy efficiency.
Publisher: MDPI AG
Date: 20-02-2019
DOI: 10.3390/EN12040682
Abstract: Power systems are the most complex systems and have great importance in modern life. They have direct impacts on the modernization, economic, political and social aspects. To operate such systems in a stable mode, several control and protection techniques are required. However, modern systems are equipped with several protection schemes with the aim of avoiding the unpredicted events and power outages, power systems are still encountering emergency and mal-operation situations. The most severe emergencies put the whole or at least a part of the system in danger. If the emergency is not well managed, the power system is likely to have cascading failures that might lead to a blackout. Due to the consequences, many countries around the world have research and expert teams who work to avoid blackouts on their systems. In this paper, a comprehensive review on the major blackouts and cascading events that have occurred in the last decade are introduced. A particular focus is given on the US power system outages and their causes since it is one of the leading power producers in the world and it is also due to the ready availability of data for the past events. The paper also highlights the root causes of different blackouts around the globe. Furthermore, blackout and cascading analysis methods and the consequences of blackouts are surveyed. Moreover, the challenges in the existing protective schemes and research gaps in the topic of power system blackout and cascading events are marked out. Research directions and issues to be considered in future power system blackout studies are also proposed.
Publisher: MDPI AG
Date: 16-03-2022
DOI: 10.3390/APP12063010
Abstract: Partial Discharge (PD) is one of the symptoms of an electrical insulation problem, and its permanence can lead to the complete deterioration of the electrical insulation in high-voltage equipment such as power transformers. The acoustic emission (AE) method is a well-known technique used to detect and localize PD activity inside oil-filled transformers. However, the commercially available monitoring systems based on acoustic sensors still have a high cost. This paper analyses the ability of low-cost piezoelectric sensors to identify PDs within oil-filled power transformers. To this end, two types of low-cost piezoelectric sensors were fully investigated using time-domain, frequency-domain, and time-frequency analysis, separately. Thereafter, the effectiveness of these sensors for PD detection and monitoring was studied. A three-phase distribution transformer filled with oil was examined. PDs were produced inside an oil-immersed transformer by applying a high voltage over two copper electrodes, and the AE sensors were coupled to the housing of the transformer. By extracting typical features from the AE signals, the PD signals were differentiated from on-site noise and interference. The AE signals were analyzed using acoustic signal metrics such as peak value, energy criterion, and other statistical parameters. The obtained results indicated that the used low-cost piezoelectric sensors have the capability of PD monitoring within power transformers.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2019
Publisher: MDPI AG
Date: 16-05-2020
DOI: 10.3390/WEVJ11020040
Abstract: The smart grid concept enables demand-side management, including electric vehicles (EVs). Thus way, some ancillary services can be provided in order to improve the power system stability, reliability, and security. The high penetration level of renewable energy resources causes some problems to independent system operators, such as lack of primary reserve and active power balance problems. Nowadays, many countries are encouraging the use of EVs which provide a good chance to utilize them as a virtual power plant (VPP) in order to contribute to frequency event. This paper proposes a new control method to use EV as VPP for providing primary reserve in smart grids. The primary frequency reserve helps the power system operator to intercept the frequency decline and to improve the frequency response of the whole system. The proposed method calculates the electric vehicles’ primary reserve based on EVs’ information, such as the state of charge (SOC), the arriving time and the vehicle’s departure time. The effectiveness of the proposed scheme is verified by several simulation scenarios on a real-world modern power system with different generating units, such as conventional power plants, renewable energy resources, and electric vehicles.
Publisher: MDPI AG
Date: 08-04-2019
DOI: 10.3390/APP9071467
Abstract: Efficient job scheduling reduces energy consumption and enhances the performance of machines in data centers and battery-based computing devices. Practically important online non-clairvoyant job scheduling is studied less extensively than other algorithms. In this paper, an online non-clairvoyant scheduling algorithm Highest Scaled Importance First (HSIF) is proposed, where HSIF selects an active job with the highest scaled importance. The objective considered is to minimize the scaled importance based flow time plus energy. The processor’s speed is proportional to the total scaled importance of all active jobs. The performance of HSIF is evaluated by using the potential analysis against an optimal offline adversary and simulating the execution of a set of jobs by using traditional power function. HSIF is 2-competitive under the arbitrary power function and dynamic speed scaling. The competitive ratio obtained by HSIF is the least to date among non-clairvoyant scheduling. The simulation analysis reflects that the performance of HSIF is best among the online non-clairvoyant job scheduling algorithms.
Publisher: Elsevier BV
Date: 11-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Institution of Engineering and Technology (IET)
Date: 28-02-2020
Publisher: MDPI AG
Date: 31-05-2022
DOI: 10.3390/FI14060172
Abstract: The automotive industry is marching towards cleaner energy in the impending future. The need for cleaner energy is promoted by the government to a large degree in the global market in order to reduce pollution. Automobiles contribute to an upper scale in regard to the level of pollution in the environment. For cleaner energy in automobiles, the industry needs to be revolutionized in all needed ways to a massive extent. The industry has to move from the traditional internal combustion engine, for which the main sources of energy are nonrenewable sources, to alternative methods and sources of energy. The automotive industry is now focusing on electric vehicles, and more research is being highlighted from vehicle manufacturers to find solutions for the problems faced in the field of electrification. Therefore, to accomplish full electrification, there is a long way to go, and this also requires a change in the existing infrastructure in addition to many innovations in the fields of infrastructure and grid connectively as well as the economic impacts of electric vehicles in society. In this work, an analysis of the electric vehicle market with the economic impacts of electric vehicles is studied. This therefore requires the transformation of the automotive industry.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: MDPI AG
Date: 07-04-2020
DOI: 10.3390/EN13071777
Abstract: To effectively guarantee a secure and stable operation of a smart substation, it is essential to develop a relay protection system considering the real-time online operation state evaluation and the risk assessment of that substation. In this paper, based on action data, defect data, and network message information of the system protection device (PD), a Markov model-based operation state evaluation method is firstly proposed for each device in the relay protection system (RPS). Then, the risk assessment of RPS in the smart substation is carried out by utilizing the risk transfer network. Finally, to highly verify the usefulness and the effectiveness of the proposed method, a case study of a typical 220 kV substation is provided. It follows from the case study that the developed method can achieve a better improvement for the maintenance plan of the smart substation.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2020
Publisher: MDPI AG
Date: 23-02-2020
DOI: 10.3390/APP10041516
Abstract: As renewable energy (RE) penetration has a continuously increasing trend, the protection of RE integrated power systems is a critical issue. Recently, power networks developed for grid integration of solar energy (SE) have been designed with the help of multi-tapped lines to integrate small- and medium-sized SE plants and simultaneously supplying power to the loads. These tapped lines create protection challenges. This paper introduces an algorithm for the recognition of faults in the grid to which a solar photovoltaic (PV) system is integrated. A fault index (FI) was introduced to identify faults. This FI was calculated by multiplying the Wigner distribution (WD) index and Alienation (ALN) index. The WD-index was based on the energy density of the current signal evaluated using Wigner distribution function. The ALN-index was evaluated using s le-based alienation coefficients of the current signal. The performance of the algorithm was validated for various scenarios with different fault types at various locations, different fault incident angles, fault impedances, s ling frequencies, hybrid line consisting of overhead (OH) line and underground (UG) cable sections, different types of transformer windings and the presence of noise. Two phase faults with and without the involvement of ground were differentiated using the ground fault index based on the zero sequence current. This study was performed on the IEEE-13 nodes test network to which a solar PV plant with a capacity of 1 MW was integrated. The performance of the algorithm was also tested on the western part of utility grid in the Rajasthan State in India where solar PV energy integration is high. The performance of the algorithm was effectively established by comparing it with the discrete Wavelet transform (DWT), Wavelet packet transform (WPT) and Stockwell transform-based methods.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Elsevier BV
Date: 07-2020
Publisher: MDPI AG
Date: 17-01-2022
DOI: 10.3390/EN15020629
Abstract: This paper made an attempt to put forward the comparative performance analysis of different energy storage devices (ESDs), such as redox flow batteries (RFBs), superconducting magnetic energy storage (SMES) device and ultra-capacitors (UCs), in the combined frequency and voltage stabilization of a multi-area interconnected power system (MAIPS). The investigative power system model comprises two areas, and each area consists of the power-generating sources of thermal, hydro and gas units. The intelligent control mechanism of fuzzy PID was used as a secondary controller optimized with a hybridized approach of the artificial electric field algorithm (HAEFA) subjected to the minimization of integral time absolute error (ITAE) objective function. However, the superiority of fuzzy PID in d ening the deviations of combined load frequency control (LFC) and automatic voltage regulator (AVR) responses was revealed upon comparison with conventional PI and PID. Further, the LFC-AVR combined analysis was extended to incorporate different ESDs one after the other. The simulation results reveal the efficacy of incorporating ESDs with the LFC-AVR system and the supremacy of RFBs in d ing out the fluctuations in frequency and voltage.
Publisher: MDPI AG
Date: 02-04-2019
DOI: 10.3390/EN12071267
Abstract: Intrinsic mode functions (IMFs) provide an intuitive representation of the oscillatory modes and are mainly calculated using Hilbert–Huang transform (HHT) methods. Those methods, however, suffer from the end effects, mode-mixing and Gibbs phenomena since they use an iterative procedure. This paper proposes an augmented Prony method for power system oscillation analysis using synchrophasor data obtained from a wide-area measurement system (WAMS). In the proposed method, in addition to the estimation of the modal information, IMFs are extracted using a new explicit mathematical formulation. Further, an indicator based on an energy and phase relationship of IMFs is proposed, which allows system operators to recognize the most effective generators/actuators on specific modes. The method is employed as an online oscillation-monitoring framework providing inputs for the so-called wide-area d ing control (WADC) module. The efficacy of the proposed method is validated using three test cases, in which the IMFs calculation is simpler and more accurate if compared with other methods.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2020
Publisher: MDPI AG
Date: 17-08-2019
DOI: 10.3390/APP9163394
Abstract: In this paper, a novel, combined evolutionary algorithm for solving the optimal planning of distributed generators (OPDG) problem in radial distribution systems (RDSs) is proposed. This algorithm is developed by uniquely combining the original differential evolution algorithm (DE) with the search mechanism of Lévy flights (LF). Furthermore, the quasi-opposition based learning concept (QOBL) is applied to generate the initial population of the combined DELF. As a result, the new algorithm called the quasi-oppositional differential evolution Lévy flights algorithm (QODELFA) is presented. The proposed technique is utilized to solve the OPDG problem in RDSs by taking three objective functions (OFs) under consideration. Those OFs are the active power loss minimization, the voltage profile improvement, and the voltage stability enhancement. Different combinations of those three OFs are considered while satisfying several operational constraints. The robustness of the proposed QODELFA is tested and verified on the IEEE 33-bus, 69-bus, and 118-bus systems and the results are compared to other existing methods in the literature. The conducted comparisons show that the proposed algorithm outperforms many previous available methods and it is highly recommended as a robust and efficient technique for solving the OPDG problem.
Publisher: Elsevier BV
Date: 11-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Springer Science and Business Media LLC
Date: 21-08-2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2021
Publisher: MDPI AG
Date: 03-04-2021
DOI: 10.3390/EN14071992
Abstract: Distribution transformer (DT) is a crucial component in power systems as it exchanges energies between different voltage levels or between utility grid and DC microgrids. Nevertheless, the operation of an oil-immersed DT is limited by the thermal and electrical capabilities of the internal insulating liquid. This paper aims to raise the efficiency of distribution transformers and preserve the environment by using a biodegradable insulating liquid instead of the conventional mineral insulating oil (MIO). This work examines the Egyptian case, where a real distribution network located in middle Egypt is selected as a pilot project. Study and analysis of the status que of the insulation system inside DTs are done with the aid of fault-tree analysis. The deficiency of the insulation system is confirmed by conducting an electronic survey of 100 expert participants. The most appropriate solution among three different alternatives is confirmed using the weighting and ranking method. The best choice suitable for the selected area is the substitution of MIO by synthetic ester (SE). The technical and environmental advantages achieved by the presented solution are discussed. The feasibility studies have proven that the solution is positively acceptable in all aspects. An execution plan is established for the application of proposed solution on the selected Egyptian distribution network.
No related grants have been discovered for Pierluigi Siano.