Journal of Operation and Automation in Power Engineering
http://joape.uma.ac.ir/
Journal of Operation and Automation in Power Engineeringendaily1Tue, 01 Aug 2023 00:00:00 +0430Tue, 01 Aug 2023 00:00:00 +0430A Novel Combined DTC Method and SFOC System for Three-phase Induction Machine Drives with PWM Switching Method
http://joape.uma.ac.ir/article_1473.html
In this paper, a novel combined Direct Torque Control (DTC) method and Stator-Flux Oriented Control (SFOC) system to increase general performances of Three-Phase Induction Motor (TPIM) drives is proposed. The introduced control scheme includes merits of DTC for instance simple structure, less dependent on PI controller coefficients, fast dynamics, and merits of SFOC such as high precision and constant switching frequency. Specifically, the proposed control scheme includes a table-based variable structure developed on DTC strategy and a PI controller in connection with a Pulse Width Modulation (PWM) algorithm based on SFOC strategy. To confirm the usefulness of the introduced controller, simulation studies are accomplished for a 2.5kW TPIM in different situations. Results under the presented control system approve the good performances of this technique in comparison with classic DTC and classic SFOC. Investigation in TPIM performances under the introduced control system indicates relatively quick dynamic responses with low torque and stator flux ripples.A New Robust Load Frequency Controller for Electric Vehicle Aggregators
http://joape.uma.ac.ir/article_1592.html
This paper proposes a robust state feedback controller for Electric Vehicle aggregators to solve the challenging problem caused by the participation of Electric Vehicles in the load frequency control of the power system.&nbsp; The Lyapunov-Krasovskii functional method is used to achieve two objectives of the robust performance and stability.&nbsp; Then, by using teaching learning based optimization algorithm, both primary and secondary participation gains of EV aggregators in LFC are optimally determined. The Generation Rate Constraint and time delay, as nonlinear elements, are also taken into account.&nbsp; Simulations are carried out on two nonlinear power systems by using the power system simulation software.&nbsp; The results show that the designed controller gives a desirable robust performance for frequency regulation at the presence of uncertainties.Risk-Based Approach for Self-Scheduling of Virtual Power Plants in Competitive Power Markets
http://joape.uma.ac.ir/article_1593.html
Dispersed energy resources and storage devices may be grouped as a Virtual Power Plant (VPP). In a competitive electricity market, VPP can exchange energy through a pool market or bilateral contracts. in order to maximize the profit, VPP needs to determine the optimal operating schedule. This paper provides a new decision-making framework based on information gap decision theory (IGDT) for robust self-scheduling of VPPs in power markets. In the proposed approach, the energy price is the uncertain parameter while the decision variables are the energy that needs to be exchanged in the pool market and through bilateral contracts, the reserve which should be provided, dispatch of distributed energy resources, the load which is needed to be curtailed, and the state of charging/discharging of energy storage devices. The proposed method specifies the self-scheduling considering the risk-taking level of the decision maker. A case study has been used to validate the proposed framework.A Review on Secondary Control Methods in DC Microgrid
http://joape.uma.ac.ir/article_1494.html
DC Microgrid is turning out to be more popular due to its appealing features such as high efficiency, excellent power quality, low cost and controllability. As the control strategies plays a key role in achieving the desired objectives such as power quality, power sharing, voltage regulation and efficiency. It is necessary to understand the classification and operation of control strategies in DC microgrids. From the control point of view, the traditional droop control methods are commonly employed for regulating proportional load sharing. However, depending on the primary control makes it challenging to maintain stable and coordinated operation in terms of maintaining both the voltage regulation and load sharing accuracy simultaneously in DC microgrids. So to avoid the trade-off in voltage regulation and power sharing accuracy, secondary control layers need to be introduced in the control structure. In this paper a review of primary control and secondary control methods (centralized, decentralized and distributed control) were discussed in detail with the classification along with the advantages and shortcomings of the control methods.A Novel Vector-Based Pulse-Width Modulation for Cascaded H-Bridge Multilevel Inverters
http://joape.uma.ac.ir/article_1595.html
The conventional space vector pulse-width modulation (SVPWM) for cascaded H-bridge inverters (CHBIs) has problems of computational complexity and memory requirements. Operation in overmodulation mode is the other reason for the complexity in SVPWM. This paper proposes a novel modulation method, named as level vector pulse-width modulation (LVPWM), for voltage control of CHBIs. The concept of the proposed method is similar to the SVPWM but with different vector diagram and dwell times calculations. Unlike the SVPWM, the &alpha; and &beta; axes and also their variables are considered separately without gathering in complex variables. The vector diagram has two separated &alpha; and &beta; axes each of which contains individual switching vectors and reference vectors. The selection of the vectors to synthesize the reference vectors depends only on the amplitudes of the reference vectors. The computational overhead and memory requirement are independent of the number of cascaded H-bridges. Lower computational overhead and easy and continuous extension to overmodulation region are the advantages of the proposed method compared with the SVPWM-based methods. Moreover, the switching algorithm achieves improved efficiency for the inverter. Simulation and experimental results verify the effectiveness of the proposed algorithm.Differential Protection of ISPST Using Chebyshev Neural Network
http://joape.uma.ac.ir/article_1598.html
An Indirect Symmetrical Phase Shift Transformer (ISPST) represents both electrically connected and magnetically coupled circuits, which makes it unique compared to a power transformer. Effective differentiation between transformer inrush current and internal fault current is necessary to avoid incorrect differential relay tripping. This research proposes a system that uses a Chebyshev Neural Network (ChNN) as a core classifier to distinguish such internal faults. For simulations, we used PSCAD/EMTDC software. Internal faults and inrush have been simulated in various ways using various ISPST parameters. A large, simulated dataset is used, and performance is recorded against different sized ISPSTs. We observed an overall accuracy greater than 99%. The ChNN classifier generated exceptionally favorable results even in case of noisy signal, CT saturation, and different ISPST parameters.A Novel Hybrid Multi-Objective Evolutionary Algorithm for Optimal Power Flow in Wind, PV, and PEV Systems
http://joape.uma.ac.ir/article_1653.html
In this paper, a new hybrid decomposition-based multi-objective evolutionary algorithm (MOEA) is proposed for the optimal power flow (OPF) problem including Wind, PV, and PEVs uncertainty with four conflicting objectives. The proposed multi-objective OPF (MOOPF) problem includes minimization of the total cost (TC), total emission (TE), active power loss (APL), and voltage magnitude deviation (VMD) as objectives and a novel constraint handling method, which adaptively adds the penalty function and eliminates the parameter dependence on penalty function evaluation is deployed to handle several constraints in the MOOPF problem. In addition, summation-based sorting and improved diversified selection methods are utilized to enhance the diversity of MOEA. Further, a fuzzy min-max method is utilized to get the best-compromised values from Pareto-optimal solutions. The impact of intermittence of Wind, PV, and PEVs integration is considered for optimal cost analysis. The uncertainty associated with Wind, PV, and PEV systems are represented using probability distribution functions (PDFs) and its uncertainty cost is calculated using the Monte-Carlo simulations (MCSs). A commonly used statistical method called the ANOVA test is used for the comparative examination of several methods. To test the proposed algorithm, standard IEEE 30, 57, and 118-bus test systems were considered with different cases and the acquired results were compared with NSGA-II and MOPSO to validate the suggested algorithm's effectivenessA New Approach for Modeling Wind Power in Reliability Studies
http://joape.uma.ac.ir/article_1600.html
Tremendous growth of wind power worldwide in the past decade requires serious research in various fields. Because wind power is weather dependent, it is stochastic and varies over various time-scales. Therefore, accuracy in wind power modeling is recognized as a major contribution for reliable large-scale wind power integration. In this paper, a method for generating synthetic wind power is proposed. The proposed method combines the random nature of wind with the operational information of the wind turbines (i.e., failure and repair rates). It uses chronological or sequential Monte Carlo Simulation (MCS) instead of non-sequential one owing to its usefulness and flexibility in preserving statistical characteristics of the chronological processes. The validity of the synthetic values generated by the proposed method and the Auto Regressive Moving Average (ARMA) time series is compared with the measured data in terms of reliability indices. Finally, the effect of some network parameters, such as network dimensions, the average coefficient of wind speed on the reliability of the power system has been evaluated. In this regard, historical wind speed data of Manjil area located in the north of Iran is used.An Improved Optimal Protection Coordination for Directional Overcurrent Relays in Meshed Distribution Networks with DG Using a Novel Truth Table
http://joape.uma.ac.ir/article_1654.html
To assure the security and optimal protection coordination in meshed distribution networks, clearing faults swiftly and selectively is an essential priority. This priority, when hosting distributed generations (DGs), becomes the main challenge in order to avoid the unintentional DGs tripping. To overcome the mentioned challenge, this paper establishes a truth table to select new settings of directional overcurrent relays (DOCRs) characteristics which can be defined by users. It concentrates on minimizing the overall relays operating time. Typically, the conventional coordination between pair relays is achieved by two settings: time dial setting (TDS) and pickup current (Ip). Besides these adjustments, the suggested approach, considered the two coefficient constant of the inverse-time characteristics, namely the relay characteristics (A) and the inverse-time type (B), as continuous to optimize. Thus, more flexibility is attained in adjusting relays features. In addition, the inclusion of user-defined settings on numerical DOCRs, not only decreases the overall operating time of relays, but also improves the performance of the backup relays against the fault points. This approach illustrates a constrained non-linear programming model tackled by the combined particle swarm optimization (PSO) and whale optimization algorithm (WOA). The efficiency of the suggested approach is assessed though the IEEE 8-bus and the distribution portion of IEEE 30-bus system with synchronous-based DG units. The obtained results demonstrate the performance of approach and will be discussed in depth.&nbsp;Data Mining Model Based Differential Microgrid Fault Classification Using SVM Considering Voltage and Current Distortions
http://joape.uma.ac.ir/article_1655.html
This paper reports support vector machine (SVM) based fault detection and classification in microgrid while considering distortions in voltages and currents, time and frequency series parameters, and differential parameters. For SVM-based fault classification, the data set is formed by analysing the operation of the standard IEC microgrid model, with and without grid interconnection, under different fault and non-fault scenarios. Fault scenarios also include different locations, resistances, and incident angles of fault. Whereas, for non-fault scenarios, the variation in load is considered. Voltages and currents from both ends of the distribution line (DL) are sampled at 1920 Hz. The time and frequency series parameters, total harmonic distortion (THD) in current and voltage, and differential parameters are determined. The SVM algorithm uses these parameters to detect and classify faults. The performance of this developed SVM based algorithm is compared with that of different machine learning algorithms. This comparative analysis reveals that SVM detects and classifies the faults on the microgrid with an accuracy of over 99.99%. The performance of the proposed method is also tested with 30 dB, 35 dB, and 40 dB noise in the generated data, which represent measurement errors.Power Spectral Density based Identification of Low frequency Oscillations in Multimachine Power system
http://joape.uma.ac.ir/article_1656.html
The paper presents a Fast Fourier Transform (FFT) based Power Spectral Density (PSD) filter for denoising the PMU signal received from the smart power system network to identify the low frequency Oscillation modes (LFO). Small disturbances are introduced during normal operation of power system causes low frequency oscillations and may hinder the power system transfer capabilities of a system. The traditional signal processing method cannot extract the information from ambient signals effectively during noisy measurement. In this paper, the performance of the Prony analysis with reduced sampling rate is analysed for the PMU data with noiseless and noise environment. It is observed that, the performance of the Prony approach is not satisfactory under noisy measurement data.&nbsp; In the present work FFT-PSD is used to denoise the noisy measurement signal and identify the nature of the decrement factor of the low frequency oscillatory modes. The accuracy of the estimated decrement factors of modes are verified with eigenvalues to validate the proposed method. The performance of proposed method is compared with signal processing method for IEEE New England power system and found effective and suitable during noisy PMU measurements.Improving the Effect of Electric Vehicle Charging on Imbalance Index in the Unbalanced Distribution Network Using Demand Response Considering Data Mining Techniques
http://joape.uma.ac.ir/article_1657.html
With the development of electrical network infrastructure and the emergence of concepts such as demand response and using electric vehicles for purposes other than transportation, knowing the behavioral patterns of network technical specifications to manage electrical systems has become very important optimally. One of the critical parameters in the electrical system management is the distribution network imbalance. There are several ways to improve and control network imbalances. One of these ways is to detect the behavior of bus imbalance profiles in the network using data analysis. In the past, data analysis was performed for large environments such as states and countries. However, after the emergence of smart grids, behavioral study and recognition of these patterns in small-scale environments has found a fundamental and essential role in the deep management of these networks. One of the appropriate methods in identifying behavioral patterns is data mining. This paper uses the concepts of hierarchical and k-means clustering methods to identify the behavioral pattern of the imbalance index in an unbalanced distribution network. For this purpose, first, in an unbalanced network without the electric vehicle parking, the imbalance profile for all busses is estimated. Then, by applying the penetration coefficient of 25% and 75% for electric vehicles in the network, charging\discharging effects on the imbalance profile is determined. Then, by determining the target cluster and using demand response, the imbalance index is improved. This method reduces the number of busses competing in demand response programs. Next, using the concept of classification, a decision tree is constructed to minimize metering time.Frequency Regulation of a Standalone Interconnected AC Microgrid Using Innovative Multistage TDF(1+FOPI) Controller
http://joape.uma.ac.ir/article_1714.html
This paper's main purpose is to offer an innovative multistage controller for load-frequency regulation of a standalone interconnected microgrid (SMG). A multistage TDF(FOPI+1) controller is designed, with the first stage being a filter built of the tilting and derivative operators. Transferring the integrator component to the second stage of the controller and employing its fractional-order (FO) form as a FO proportional-integrator (FOPI) controller results in the latter stage of the controller. To calculate the optimal controller parameters, the recently introduced Bonobo optimization algorithm (BOA) is applied. Besides, the optimization objective function is a mix of the control error signal in each area and the dynamic response characteristics of the system. In complex operating conditions such as sudden changes in power demands, uncertainties in renewable energy units' output, considering nonlinear factors, and parametric uncertainties in a two-area SMG, the performance of the proposed controller is compared with classical and multistage controllers. The results show that the TDF(1+FOPI) controller has a competent dynamic response and can be a suitable choice for performing LFC duties in SMGs. This control strategy's advantages include enhanced controller resistivity in diverse circumstances, faster reaction times, and better dynamic behavior. The results of the five studied scenarios show that using the proposed control strategy, the value of the objective function is improved by an average of more than 50% compared to other classical and conventional controllers. Similarly, improvements of more than 70% and 50% in key integral of time-weighted square error (ITSE) and Integral of absolute error (IAE) time zone indicators, respectively, are among the results of these studies.Power Quality of Electric Vehicle Charging Stations and Optimal Placement in the Distribution Network
http://joape.uma.ac.ir/article_1754.html
Due to the presence of power electronic converters in electric vehicle battery chargers, the electrical power drawn from the distribution system has severe distortions which pose many problems to the power quality. Herein, the impact of chargers in terms of indicators, e.g., penetration level, battery state of charge, type of charging stations, the time of connection of chargers to the network, and the location of charging stations was comprehensively studied on a sample distribution network. The effect of these chargers was investigated based on power quality parameters, e.g., total harmonic distortion (THD) and voltage profile, and the effect of each indicator on these parameters was determined. To minimize the effects of the chargers, an IEEE 33-bus distribution sample network was optimized with the objective functions of voltage drop and THD. Based on this optimization algorithm, the installation placement and the power capacity of the charging stations were obtained to achieve the lowest voltage drop and THD.Optimal Scheduling of Electrical Storage System and Flexible Loads to Participate in Energy and Flexible Ramping Product Markets
http://joape.uma.ac.ir/article_1755.html
The power systems operation has encountered some challenges due to the increasing penetration rate of renewable energy sources. One of the main challenges is the intermittency of these resources, which causes power balance violations. On the other hand, there are various distributed energy resources (DERs) to compensate for the need for the ramp capacity. Hence, to indicate this issue, the energy storage systems and the heating, ventilation, and air conditioning (HVAC) loads are selected in the form of a DER aggregator (DERA) to participate in the day-ahead (DA) energy and flexible ramping product (FRP) markets in this paper. Therefore, a co-optimization method is used to model the aggregator&rsquo;s decision-making, as a mixed-integer linear programming (MILP) approach, in both the markets. The obtained results revealed that the profit of the DERA increases by considering not only its participation in the joint energy and FRP markets but also the potential of the HVAC loads. Moreover, the accuracy of the model is investigated using the sensitivity analysis of the parameters, including deployment probability, customers&rsquo; welfare, and the allowed temperature deviation. High Gain DC/DC Converter Implemented with MPPT Algorithm for DC Microgrid System
http://joape.uma.ac.ir/article_1756.html
This paper presents the output voltage control and execution of a novel non-isolated high step-up (NIHS) DC-DC converter connected to a solar photovoltaic (PV) based DC microgrid system. The proposed converter provides a high output voltage conversion ratio over smaller duty cycles, small inductors, low cost, and high efficiency to enhance the level of the generated voltages of PV. Also, to overcome the drawback of PV, the detailed operation of maximum power point tracking (MPPT) for the novel boost DC-DC converter topology is presented. A control algorithm, modified perturb and observe (MP&amp;O), is put forward to assure that the maximum power is extracted from PV at any environmental condition. It regulates the output voltage of the PV system to the desired DC bus voltage. This technique is compared with the Incremental Conductance (INC) and conventional P&amp;O algorithm in terms of their computational complexity and oscillations near maximum power point (MPP) using MATLAB &amp; Simulink. The focus is on the continuous conduction mode of the proposed converter. To demonstrate the effectiveness of the proposed converter, operation modes, and technical analysis are conducted. Also, the experimental results of a 200 W-12V/120V, 25 kHz prototype are given and discussed to justify the suggested converter.A New Transformerless DC-DC Converter for Renewable Energy Applications
http://joape.uma.ac.ir/article_1757.html
In this paper, a novel high step-up voltage switching cell formed by four passive elements and three diodes is proposed. The proposed cell can be integrated into a family of boost converters to obtain substantial dc gain as required by an electrical grid supplied such as solar or fuel cell. It is integrated into a boost converter; a new converter is obtained. The features of a new converter are significant dc gain without extreme duty cycle which enables the use of lower voltage and R${}_{Ds-on}$ MOSFET switch so as to reduce cost, the low-stress voltage on the switch and diodes, non-pulsating input current, easiness design and operation, single switch which means easiness of transistor driving, and line-load common ground. In addition, the low-voltage stress across diode allows using Schottky rectifiers to eliminate the reverse recovery current which leads to more reduction in conduction and switching losses. The equations of voltage and current in "continuous conduction mode (CCM) and discontinuous mode (DCM)" are extracted. Moreover, the voltage and current stresses on elements and switch are calculated. Finally, the performance of the proposed converter is validated by simulation results and experimental results to confirm theoretical calculation.A Decentralized Energy Management Method for Load Curve Smoothing Considering Demand and Profit of Electric Vehicle Owners with Different Capacity of Batteries
http://joape.uma.ac.ir/article_1758.html
Increasing requirements of electric vehicles with different capacities of batteries and increasing number of small-sized renewable energy sources lead to complexity of calculations, voltage drop, power quality loss, and unevenness in the load curve. This paper proposes a modified version of the mean-field decentralized method to smooth the load curve, maximize vehicle owners' profit, and meet vehicle owners&rsquo; demands. Different capacity of batteries is a challenging problem in the charging and discharging control of electric vehicles; so to solve this problem, a weighted average method is used, which determines the design weighting parameters based on the capacity of batteries. Finally, a comparison has been made between five different centralized and decentralized strategies with weighted and weightless average methods.A MILP Model Incorporated With the Risk Management Tool for Self-Healing Oriented Service Restoration
http://joape.uma.ac.ir/article_1761.html
The inevitable emergence of intelligent distribution networks has introduced new features in these networks. According to most experts, self-healing is one of the main abilities of smart distribution networks. This feature increases the reliability and resiliency of networks by reacting fast and restoring the critical loads (CLs) during a fault. Nevertheless, the stochastic nature of the components in a power system imposes significant computational risk in enabling the system to self-heal. In this paper, a mathematical model is introduced for the self-healing operation of networked Microgrids (MGs) to assess the risk in the optimal service restoration (SR) problem. Electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) and their stochastic nature besides the distributed generation units (DGs), the ability to reconfiguration, and demand response program are considered simultaneously. The objective function is designed to maximize the restored loads and minimize the risk. The Conditional Value-at-Risk (CVaR) is used to calculate the risk of the SR as one of the most efficient and famous risk indices. In the general case study and considering $\beta $ equal to the 0, 1, 2, 3, and 4, expected values of SR for the risk-averse problem is 21.2, 20, 19.3, 19.1, and 19\% less than the risk-neutral problem, respectively. The formulation of the problem is mixed-integer linear programming (MILP), and the model is tested in the modified Civanlar test system. The analysis of several case studies has proved the performance of the proposed model and the importance of risk management in the problem.A New Single-Phase Single-Stage Boost Inverter for Photovoltaic Applications
http://joape.uma.ac.ir/article_1792.html
In this paper, a new single-phase single-stage high step-up boost inverter appropriate for photovoltaic systems is proposed. In the proposed inverter, the duty cycle of one of the switches is adjusted to control the output voltage and increase the gain. In this structure, the dynamic model is adopted as an appropriate model to describe the low-frequency behavior of converters and extract the equations. Moreover, in this topology, a common ground is used between the input and output which can remove leakage current in different applications, including grid-connected applications. The proposed inverter is simulated using MATLAB/SIMULINK, and the experimental results are presented to verify the theoretical analysis.Stability Analysis of Microgrid with Passive, Active, and Dynamic Load
http://joape.uma.ac.ir/article_1793.html
The autonomous microgrid can incur a stability issue due to the low inertia offered by power electronics-based distributed generating sources of the microgrid. Due to the fast dynamics of inverters and the intermittent nature of renewables, the first phase of abrupt load change might not be shared evenly by DGs, and the system's stability deteriorates substantially. Hence the stability of the microgrid can greatly influenced by the load dynamics because of the inertialess generating sources. This paper presents a stability analysis of microgrid considering passive, active, and dynamic loads fed by inverter-based DGs. The small-signal analysis demonstrates the effect of inverter parameters and load factors. The dominance of states in oscillatory mode is examined by participation analysis. The results show that passive load does not introduce low-frequency mode, whereas rectifier interfaced active load (RIAL) introduces low-frequency mode due to DC voltage controller. The induction motor (IM) load introduces less damped eigenvalues in the microgrid and profoundly affects the real power-sharing of the system. The time-domain results verify the results obtained through eigenvalue analysis.