Journal of Operation and Automation in Power Engineering
Volume:12 Issue: 1, Spring 2024

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.

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.  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.

Due to the development of renewable energy and the need for sustainable electricity, AC microgrids (MGs) have received a lot of attention and the growing need for them is becoming more and more apparent. Medium voltage MGs will be very important in providing electrical energy in the near future. This paper represents a robust and effective control method with rather simple implementation capability for islanded MGs based on master-slave (MS) technique. The designed control is a type of terminal sliding mode control, which has a high response speed and good convergence with robustness against some uncertainties. Stability and high performance are very essential for islanded MGs. The designed control meets these requirements so that the output voltage of the inverter based distributed generation (DG) sources includes a very low amount of harmonics and the generated active and reactive powers track their reference values perfectly. The effectiveness of the proposed control method is evaluated by simulation in SIMULINK/MATLAB environment. The simulation results are presented considering five cases, which include feedback linearization control (FLC) and conventional sliding mode control (CSMC) of DGs, harmonic load and high impedance transmission lines simulation results. The obtained results show the perfect  tracking  and  robustness  of  the proposed control scheme considering uncertainties in parameters and it is illustrated that a high accuracy power sharing between DG sources is achieved.

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.

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.

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.

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.

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.