Journal of Operation and Automation in Power Engineering
https://joape.uma.ac.ir/
Journal of Operation and Automation in Power Engineeringendaily1Sun, 01 Oct 2023 00:00:00 +0330Sun, 01 Oct 2023 00:00:00 +0330An Improved Optimal Protection Coordination for Directional Overcurrent Relays in Meshed Distribution Networks with DG Using a Novel Truth Table
https://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
https://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
https://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
https://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.Power Quality of Electric Vehicle Charging Stations and Optimal Placement in the Distribution Network
https://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
https://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
https://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 Decentralized Energy Management Method for Load Curve Smoothing Considering Demand and Profit of Electric Vehicle Owners with Different Capacity of Batteries
https://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.Frequency Regulation of a Standalone Interconnected AC Microgrid Using Innovative Multistage TDF(1+FOPI) Controller
https://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.A New Transformerless DC-DC Converter for Renewable Energy Applications
https://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 MILP Model Incorporated With the Risk Management Tool for Self-Healing Oriented Service Restoration
https://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
https://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
https://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.Torque Ripple Reduction of the Position Sensor-less Switched Reluctance Motors Applied in the Electrical Vehicles
https://joape.uma.ac.ir/article_1797.html
The Switched Reluctance Motors (SRMs) not only are low cost for industry applications, but &lrm;also they could work in various conditions with high reliability and efficiency. However, usage &lrm;of these motors in high speeds applications under discrete mode causes decreasing the &lrm;efficiency. In this paper, a new optimized control method based on the various Torque Sharing &lrm;Functions (TSFs) and optimization algorithms is proposed for Minimum Torque Ripple Point &lrm;Tracking (MTRPT) of a 4-phase SRM with 6/8 poles. In this method, turn-on and commutation angles are controlled based on the lookup table. The proposed method could adjust the rapid variations of the current in the starting mode of SRM. To show the robustness of the proposed approach, a real case study is considered, the control method is applied in an Electric Vehicle (EV) mechanism, and its performance is assessed in various motion states such as acceleration, breakage, and steady-state. Also, the position sensor for the studied EV is &lrm;neglected, which could reduce the extra costs. There are two various scenarios considered for solving the problem. First, the turn-off and turn-on angles are controlled, and the commutation angle is fixed. The results show the &lrm;robustness of the proposed method with about 90 \% diminishing the torque ripple, compared to &lrm;when all mentioned angles are fixed. In the second step, based on a lookup table, instead of using &lrm;complex analytical methods, the turn-on angle is controlled. Therefore, a variable turn-on &lrm;angle &lrm;proportional to the applied speed is applied to the commutation control system of SRM. Besides, &lrm;a lookup table is created to restrain the reduction of the turn-off angle. The simulation results are &lrm;compared to other previous methods, and the worth of the proposed method is shown.&lrm;Optimal Sizing of Distributed Power Flow Controller Based on Jellyfish Optimizer
https://joape.uma.ac.ir/article_1798.html
In the family of Flexible AC Transmission Systems (FACTS) controllers, the distributed power flow controller (DPFC) can control powerfully all the system's parameters like bus voltages magnitude, transmission angle, and line impedances with high redundancy and a wide range of compensation. In this paper, IEEE-14 bus IEEE-30 bus, and IEEE-118 bus systems are taken for the testing of the proposed approach. The optimal placement of the series and shunt converters of the DPFC is decided by the most critical bus and most critical line associated with that bus respectively. The sizing of the DPFC is decided based on the minimization of active power losses of the systems. The loss function is considered an objective function and the limits of the bus voltages magnitudes, bus voltage angles, thermal limits of the lines, and level of compensation of the DPFC are taken as the system's constraints. To solve complex problems in various fields, meta-heuristic optimizations are more popular. Among the meta-heuristic optimizers, the jellyfish optimizer is one that is based on the behavior of jellyfish in the ocean. The optimization of the objective function with constraints has been solved by time-varying acceleration coefficients (TVAC) particle swarm optimization (PSO), artificial bee colony (ABC), genetic algorithm (GA), and metaheuristic optimizer jellyfish methods. Results show that all the optimization techniques provide solutions with minimum losses. Among these methods, the solution of the jellyfish optimizer has the lowest active power losses, highest convergence rate, less number of iterations, and also takes less computational time.Providing Control Method Using UPQC and Wind Turbine to Reduce Voltage Drop and Harmonics During Distribution Network Faults
https://joape.uma.ac.ir/article_1801.html
Existing generators used in renewable wind Turbines (WT) that are connected to the power system at the distribution level need a sound power grid for proper operation. The purpose of this article is to simultaneously use Unified Power Quality Conditioner (UPQC), wind turbine and appropriate control system to achieve the lowest harmonic distortion and voltage drop during network faults. Also, in this article, in order to check the efficiency of different fact tools when there is a fault in the network, a comparison between UPQC performance with static VAR compensator (SVC) and distribution synchronous static compensator (D-STATCOM) was made and the obtained results were presented. The performed simulations are based on compensation of voltage decrease and increase as well as compensation of harmonic distortion caused by nonlinear loads. The results obtained in this article show that Using UPQC in the network was able to compensate for 100% of voltage drop and voltage increase in the network, while svc and D-Statcom equipment in the best case compensated for 98\% of voltage increase and 90\% of voltage decrease. UPQC also can be the best tool to eliminate network flow harmonics. &nbsp;In the previous papers, the best value for harmonic current distortion was 1.67%, but our results showed that the harmonic distortion of the network current when using UPQC is 1.47%. Also the harmonic distortion of network current with SVC and D-Statcom is 5.67 and 4.87 percent, respectively. The capability of the equipment in compensating for short circuit fault current and protection of wind power plant is also evaluated. There was no change in wind turbine voltage during the use of UPQC and faults, and 1 P.U remained constant, but when using svc and D-Statcom equipment, the wind turbine voltage during the fault decreased by 0.3 and 0.5 P.U respectively.Comparison of Transmission Line Models by Excluding Frequency Dependence in Complex Power System for Error Estimation
https://joape.uma.ac.ir/article_1802.html
Today, commercial simulation packages can have the capability of solving complex power system networks by using various transmission line models. When there is a change in the modeling routine of transmission lines, their accuracy is also changese main aim of this paper is to compare lumped PI and distribute CP transmission line models in terms of accuracy and optimization capability. The IEEE 57 bus time domain power system models are designed by using these transmission line models for analysis in this paper. In these proposed systems the transmission line parameters are described as frequency independent. Therefore, in CP lines the Clark's transformation method does not provide exact decoupling of lines, to achieve exact decoupling of lines and accuracy the lines are continuously transposed in proposed systems. The NR load flow analysis was used for error estimation in balanced and unbalanced networks. The results had reported voltage error at the buses, transmission line error as function of line length and frequency response of line parameters. The frequency study of the line parameters was shown the PI lines system behaves as low pass filter and the CP lines system behaves as high pass filter. In this paper, also studied the optimization of proposed models by using a well-known Ant Lion Optimization (ALO) algorithm to set control variables, such as generator voltages, position of tap changing transformers and shunt capacitor banks. The optimization results of total power loss, voltage deviation and voltage stability index were compared with other algorithms. The results revealed that the ALO has best cothe nvergence characteristics and best elitism phase. Therefore, the CP lines system had shown considerable improvements of optimization results.A Sampling Method based on System State Transition for Distribution System Adequacy Assessment using Distributed Generation
https://joape.uma.ac.ir/article_1803.html
A sampling method is proposed related to-system state transition based Monte Carlo simulation (SSTMCS) for the adequacy assessment in the radial distribution system (RDS) in the presence of distributed generation (DG) termed as a composite distribution system (CDS). This method evaluates well-being indices such as probabilities, frequency, and duration indices in healthy, marginal, and risky states. A deterministic criterion is used for adequacy assessment. Samples are generated using a load flow program for RDS used in SSTMCS. The loss sensitivity factor is utilized for the positioning of DGs in RDS. DG capacity and load at buses are considered continuous random variables. Different cases are addressed to demonstrate the impact of varying DG capacities on well-being indices. Moreover, the results are compared with the state enumeration method (SEM). IEEE-33 bus RDS is considered for this study.Improved Power System Dynamic Stability by DFIG in the Presence of SSSC Using Adaptive Nonlinear Multi-Input Backstepping
https://joape.uma.ac.ir/article_1806.html
In this paper, Doubly Feed Induction Generator (DFIG) improves the dynamic stability of the power system in the presence of Static Synchronous Series Compensator (SSSC) using nonlinear control theory. The control method used in this study is based on the nonlinear multi-input adaptive backstepping control. The control signals are assigned to DFIG and SSSC and synchronous generator excitation system. The applied control method is more effective than the conventional linear and nonlinear ones which are reported in the literature. Also in this study, control inputs are designed considering their appropriate constraints. The controller coefficients are optimally selected using intelligent algorithms that increase the performance of the controller in terms of achieving stability. The designed control is robust against parameter variations and load changes as well as changing in the location of the disturbances. This method is simulated in two aspects of the synchronous machine model as a third-order model and a second-order one. The methods are implemented on a 39-bus IEEE system and the simulation results show the effectiveness of the proposed control mechanism.Optimized Cost of Energy by a Home Energy Management System Employing Dynamic Power Import Limit Strategy: A Case study Approach
https://joape.uma.ac.ir/article_1899.html
Nowadays, the centralized power system is changing to a distributed system, and various energy management systems are being installed for efficient functioning. Load side management is a vital aspect of the energy management of the power network. As residential demand is growing at a high rate, domestic customers play a crucial role in the successful implementation of demand response (DR) programs. This paper considers a single customer having a home energy management system (HEMS) for thermostatic and non-thermostatic characteristics-based appliances, photovoltaic panels, an electric vehicle, and a battery energy storage system. The effect of various DR strategies has been discussed. A mixed-integer linear programming-based model of a HEMS is modulated and solved to minimize the electricity consumption cost by employing a real-time price-based DR program using dynamic power import limits. An incentive-based DR program is considered for reducing the energy demand and maintaining the energy balance during peak hours, and peak pricing-based dynamic power import limiting DR programs are included for load shaping. The effect of load shaping on the peak to average ratio is also discussed in different scenarios. Finally, the total electricity price is calculated and analyzed by considering other test cases based on the inclusion/rejection of the mentioned DR programs.Robust stochastic blockchain model for peer-to-peer energy trading among charging stations of electric vehicles
https://joape.uma.ac.ir/article_1900.html
Fossil-fueled vehicles are being replaced by electric vehicles (EVs) around the world due to environmental pollution and high fossil fuel price. On the one hand, the electrical grid is faced with some challenges when too many EVs are improperly integrated. On the other hand, using a massive unexploited capability of the batteries in too many EVs makes these challenges opportunities. This unused capacity can be employed for the grid ancillary services and trading peer-to-peer (P2P) energy. However, the preference of EV users is one of the most important factors, which has to be considered within the scheduling process of EVs. Therefore, this paper proposes a stochastic model for EV bidirectional smart charging taking into account the preferences of EV users, P2P energy trading, and providing ancillary services of the grid. Considering the likings of EV users makes the proposed scheduling model adaptive against changing operating conditions. The presented model is formulated as an optimization problem aiming at optimal managing SOC of EV battery and electrical energy placement of several facilities considering the provision of ancillary services and contributing to P2P transactions. To evaluate the proposed model, real-world data collected from Tehran city are used as input data for simulation. Numerical results demonstrate the ability of the presented model. Simulation results display that considering the preferences of EV users in the proposed model can enhance the total income provided by the EV energy-planning model such that it could balance the charging cost. Moreover, this advanced user-based smart charging model increases P2P energy transactions amongst EVs and raises the ancillary services facility to the grid. Simulation results show that the yearly cost of optimal electrical charging on normal trips, light trips, and heavy trips is reduced by 32.6%, 51.2%, and 34.8% compared to non-optimal ones, respectively.Robust Self-Scheduling of PVs-Wind-Diesel Power Generation Units in a Standalone Microgrid under Uncertain Electricity Prices
https://joape.uma.ac.ir/article_1901.html
In the semi-autonomous regions and remote islands, the multiple diesel units are usually used for supplying demand and exchanging power with other adjacent zones. In the risk-aware generation companies consisting of diesel engines, photovoltaic panels (PVs), and wind turbines, the uncertain electricity market prices affect the optimum operating points of these units, the total revenue gained from selling energy to neighbor microgrids, and the daily fuel cost of the diesel generators. Moreover, the output power of the diesel engines is a nonlinear function of their specific fuel consumption at discrete loading intervals. Therefore, this paper aims to present a risk-aware mixed integer nonlinear optimization problem for finding the best generation schedules of the diesel units involving the energy price fluctuations. The total fuel costs of the diesel engines minus the total revenue achieved from procuring power for nearby regions is minimized as a cost objective function satisfying the lower and upper generation bounds in each loading subinterval, the load-generation balance criterion, and the nominal capacities of generating units. The cubic spline interpolation is used for accurately fitting the fuel-power curves of the diesel generators at successive loading subintervals because of its zero norm of residual in comparison with 5${}^{th}$ degree and quadratic polynomials. A benchmark microgrid with six diesel generators, PVs and wind turbines is robustly scheduled using the budget of uncertainty with no need to probability distribution and membership functions of energy prices. It is revealed that this strategy is practical for each price-taker generation company, which desires the risk-aversion production patterns of the diesel power production units against the energy market price uncertainty in a specific operating horizon.A Real-time Condition Monitoring-based Asset Management Model for Power Transformers in the Presence of Distributed Generation
https://joape.uma.ac.ir/article_1902.html
With the advent of advanced measurement and supervisory devices in power systems, wide area measurement systems and real-time monitoring of power systems have become viable. Accordingly, modeling techniques should be updated as well. This paper proposes a transformer asset management model based on real-time condition monitoring in the presence of distributed generation. The model is tested under different case studies and compared with the previous models in which constant failure rate model was used for asset management of transformers. The system cost includes operation, repair, and interruption costs. The objective is to determine the hourly loading of the transformer so that the cost of system is minimized. The long-term objective is to determine the loading pattern of the transformer which guaranties the most economical pattern among various options. Results showed that the proposed model is efficiently capable of returning more accurate responses if real-time monitoring data is used. A set of sensitivity analysis studies are also performed to highlight the impact of each factor separately. The contribution of distributed generators to supply the load is also investigated. Results showed that the use of distributed generators reduces the overall cost of the system by diminishing the risk-based element of the system cost.A DC-DC Converter with High Voltage Conversion Ratio Recommended for Renewable Energy Application
https://joape.uma.ac.ir/article_1903.html
In this article, a novel topology of DC-DC converter based on voltage multiplier cell and coupled inductor with higher efficiency and low blocking voltage across semiconductor is proposed for renewable energy application. The recommended topology obtains a high voltage gain using voltage multiplier cell and one coupled inductor. Only one power switch is utilized in this structure, which reduces the converter's cost. The other benefits of this converter are low number of components, high efficiency due to the zero-voltage switching and the zero-current switching of diodes, and low blocking voltage of the power switch and diodes. Besides, the voltage multiplier cell acts as a passive clamp circuit and reduces the voltage stress across the power switch. Thus, a low rated power switch can be used in the presented topology. Due to the zero-current switching in Off-state, the reverse recovery problem of diodes is reduced. To illustrate the performance and superiority of the presented topology, operation modes, steady-state and efficiency analysis, and the comparison study with other similar converters are presented. Finally, a 160~W experimental prototype with 50~kHz switching frequency and 17 V input voltage are built to confirm the theoretical investigation and effectiveness of the proposed converter.Optimizing Multi-objective Function for User-Defined Characteristics Relays and Size of Fault Current Limiters in Radial Networks with Renewable Energy Sources
https://joape.uma.ac.ir/article_1908.html
Installing the renewable energy sources (RESs) in distribution networks changes the fault current direction, increases the fault current level and, consequently, eliminates the protection coordination between the protective devices. Overcurrent relays are among the most important protective devices in distribution networks. Proper performance of the protective system requires protection coordination between the overcurrent relays. The present paper proposes a new protection coordination scheme using digital directional overcurrent relays (DOCRs) and dual-setting digital overcurrent relays (DS-DOCRs) in the distribution network in the presence of the RESs and energy storage systems (ESSs). For this purpose, a multi-stage objective function was used. In the first stage, a weighted objective function was employed to optimize the size and location of the RESs as well as the location and impedance of the FCLs in order to reduce the loss, improve the voltage profile and decrease the variation of the feeders' currents at the connection time of the RESs. In the second stage, DOCR and DS-DOCR settings optimization, which included parameters A and B in addition to parameters I${}_{p}$ and TDS, was used to restore the lost protection coordination for the fault current in the shortest possible time. The simulation results on the IEEE 33-bus network in the presence of RESs using genetic algorithm and PSO algorithm method as well as DPL programming language in DIgSILENT software showed that the total operating time of digital relays and network loss were reduced and voltage profile was significantly improved.Bi-level programming of retailer and prosumers' aggregator to clear the energy of the day ahead using the combined method of mixed integer linear programming and mayfly optimization in smart grid
https://joape.uma.ac.ir/article_1909.html
In the restructured electricity industry, the electricity retailer, as a profit-oriented company, buys electricity from wholesale electricity markets and sells it to end customers. On the other hand, with the move of the electricity networks towards smart grids, small customers who, in addition to receiving energy from the distribution network, can generate power on a small scale, have emerged as prosumers in the electricity market environment. Therefore, the prosumers' aggregator is defined to maximize the profit of a set of prosumers in this environment. In this paper, the energy exchange between the retailer and the aggregator has been modeled as a bi-level game. At a higher level, the retailer, as a leader to maximize its profit or minimize its expenses, offers a price to buy or sell energy to the prosumers' aggregator. The aggregator also decides on the amount of exchange energy to buy or sell, to minimize the energy supply costs required of its consumers according to the retailer's bid price. In this paper, a combined method based on~MILP (Mixed Integer Linear Programming)~and MO (Mayfly Optimization) has been used to find the optimal point of this modeled game. To evaluate the efficiency of the proposed method, the three pricing methods FP (Fixed Pricing),~TOU (Time Of Using), and RTP (Real Time Pricing) as price-based demand response programs have been compared using the proposed algorithm. The simulation results show that among the three pricing methods for customers, the RTP pricing method has the highest profit for the retailer and the lowest cost for the aggregator.Investigation of Stray Losses in Converter Transformer Using Parametric Analysis of Wall Shunt Thickness
https://joape.uma.ac.ir/article_1910.html
In High Voltage Direct Current Transmission (HVDC) system, converter transformer is an integral part of the system. Generally, core loss, copper loss and stray losses occur in the transformer. &nbsp;In which stray losses are produced in the transformers metallic parts such as transformer tank which can be 10\% to 15\% of the total loss. Experimentally, stray losses are difficult to measure. So, it is essential to use numerical modelling to predict the stray loss. The secondary winding of the converter transformer is directly linked to the rectifier or inverter. As a result, the converter transformer winding's current is non-sinusoidal. Due to non-sinusoidal current, losses are more in converter transformer than in~the power transformer. This article analyses the stray loss reduction techniques by applying wall shunt on the transformer tank surface. These stray losses are estimated for different wall shunt thickness values by varying the thickness of wall shunt using parametric analysis in 3-D finite-element analysis (FEA). Two types of wall shunts is used:-horizontal and vertical. In which horizontal wall shunt results are compared with the vertical wall shunt for non-sinusoidal and sinusoidal current excitation, where sinusoidal excitation is a fundamental component of non-sinusoidal excitation. For a case study, 315 MVA converter transformer is used to estimate stray losses on this transformer. The results obtained by the numerical method are also compared with the analytical method. Result shows that the stray losses are decreased with an increase in wall shunt thickness. Also, these losses are less for sinusoidal excitation than the non-sinusoidal excitation.