Research and Technology in Electrical Industry
Volume:1 Issue: 1, Winter 2022

The reliability level of the distribution network is a judgment tool of the grid and protection design quality, the effectiveness of the fault management unit, and customers’ satisfaction. In this paper, a new approach is presented to evaluate common reliability indices namely ENS, SAIDI, SAIFI, MAIFIe, etc., while reliability improvement via optimal post-fault restoration describes the coordinated operation of various protection and control devices in temporary and permanent fault event conditions. Customers’ outage times are calculated considering different switching operation times to capture manual operation issues, e.g., traffic level, geographical issues, fuse replacements, etc. The optimal service restoration scheme being formulated in a mixed-integer linear programming (MILP) fashion is constrained to network technical limitations, e.g., line thermal capacity, load points voltage level, DG units’ parameters, and island operation. Performance of the proposed framework is verified in IEEE 33-bus test system.

Nowadays, with increasing penetration of Induction Generators (IG) in the electricity grid, it is of great importance that IG be connected to the grid in the fault conditions. In this paper, a terminal voltage based method for transient stability study of IG is proposed. For this purpose, an improved analytical method is used to determine Critical Clearing Time (CCT) of IG in the state of grid fault, including near and non-near faults. For the faults occurring far from the terminal of generator, electromagnetic torque is not equal to zero during fault. Hence, equivalent circuit model of IG and network is used to calculate the CCT. A new formulation based on terminal voltage of IG is presented to consider the stability constraint on Over Current Relay (OCR) coordination, to prevent disconnecting of IG in grid fault condition. Simulations are carried out on two samples network, and the results demonstrate the efficiency of proposed method.

Recent weather-related disasters experienced worldwide with considerable damages to the interconnected power infrastructure have highlighted the importance and urgency of enhancing the resiliency of the distribution grid. A Resilient distribution grid can withstand and recover from such rare events. Resiliency against extreme events is conceptualized in three distinct stages: prior, during, and after the event. Rapid recovery is a feature of after the event stage. In this paper, restoration strategies to restore maximum loads as quickly as possible are investigated. The proposed approach attempts to restore the critical loads by using tie-switches to reconfigure the network. In the case of isolated areas without the possibility of using upstream utility grid, sectionalizing the grid into several microgrids (MGs) is proposed to improve the system resiliency. The number of isolated MGs is an issue that is required to be correctly determined. So, a new approach is proposed to compromise between amount and reliability of supplied load to find the optimum number of MGs. The proposed method is simulated on the unbalanced IEEE-123 and 37-bus distribution grid with random locations for DERs.

Power system flexibility is an important characteristic in both power system planning and operation, which should be evaluated and maintained in the desired value. On the other hand, more renewable energy integration leads to increasing uncertainty and variability in the power system. Therefore, the power system should have the sufficient ability to overcome the adverse effects of uncertainty and variability named as flexibility, which should be improved by suitable tools such as adequate reserve, fast ramp up/down generation sources and suitable energy storage capacity. Power system flexibility evaluation is the main task that needs suitable indices to indicate the level of system flexibility correctly. In the current paper, a well-known system flexibility index named normalized flexibility index, which is used for power system planning horizon is modified to use for the operational planning time zone. In this concept, the flexibility index is separated into two components, each of them indicating the ability of the power system to withstand upward/downward net-load uncertainty and variability. In the further, this is shown these two components are the same as the upward/downward system reserve and can be converted to economic value simply. So, this concept facilitates the economic trade-off between operation cost and system flexibility, improving cost to achieve the best level of system flexibility.

Achieving high distribution-reliability levels and concurrently minimizing operating costs are as the main issues in distribution system optimization. Determination of the optimal number and location of remote control switches (RCS) in the distribution system network is an essential issue from the reliability and economic points of view. To address these issues, this paper develops a novel multiobjective model from the distribution system viewpoint, wherein the primary objective, optimal RCS placement is implemented aiming at minimizing the operating costs, while in the second objective, the reliability index improvement is taken into account. So, a novel approach from a robust heuristic algorithm, modified non dominated sorting genetic algorithm (MNSGA-II), is developed and presented to solve this multiobjective mixed-integer non-linear programming problem. Simulation results received by the genetic algorithm have been compared with the other popular optimization algorithms, seperately. Results show that the proposed algorithm provides extensively the best performance, in terms of quality of the answer received and computational efficiency. The feasibility of the proposed algorithm was examined by application to two distribution feeders of the Tabriz city distribution network containing the fourth feeder of the TractorSazai substation.

Global Warming and progression of modern power networks have profoundly changed traditional power grids in terms of fossil fuel consumption and emission of toxic gases. Therefore, auxiliary power plants and ancillary services have been introduced as an effective alternative, to overcome these new challenges in power systems. In this work, the dynamic environmental economic dispatch (DEED) problem, is investigated by considering the plug-in electric vehicles (PEVs), minimizing the fuel cost and greenhouse gas emissions from fossil fuel units. In the mentioned problem, to make it more practical, various operational constraints, including valve-point loading effect (VPLE), ramp rate limits (RRLs) and generation capacity limits are considered. This paper proposes a new multi-objective exchange market algorithm (EMA) based on the non-dominated sorting theory to find the Pareto front. In addition, the impacts of PEVs, as an uncertainty source, on the mentioned problem are analysed in four different charging scenarios. The efficiency of the proposed method has been detailed on three experimental systems and the obtained results are compared with other algorithms in this field. The results show that the maximum percentage reduction in costs for test cases 1 to 3, are about 2.13, 2.69, and 39.48, respectively, and bout 45.96, 48.20 and 44.07, for emission, respectively. The comparative analysis verify the proposed method efficiency, and accuracy in solving the suggested problem.

Resonance and ferroresonance in power systems are categorized as two destructive phenomena especially in HV networks which their occurrence are being initiated in consequence of a power system event. Also, Ferroresonance phenomenon may be initiated by non-power system event such as lightning strike. Hence, the study of resonance and ferroresonance requires an exhaustive evaluation of possible network events in different network configurations. In each event, the analysis of network voltages is conducted based on identified allowable limits by IEEE 519 standard as an evaluation critera. In this paper, a novel comprehensive study approach is proposed for study of ferroresonance phenomena in power networks. The proposed approach comprises different steps including substation equipment modeling, EMT simulation of the probable switching events, evaluation of correspondence results, and finally detecting the probable ferroresonance occurrence. Furthermore, a novel approach for resonance study is also presented. Voltage and current limits are implemented to define an impedance criteria for performing resonance evaluation of network buses. Findings – The proposed method is implemented for study of resonance and ferroresonance in all HV substations of the Khuzestan regional electricity network. By performing the proposed evaluations, the probable condition which may lead to resonance and ferroresonance occurrence are identified. The results are highly valuable for network operators in prevention of unintended overvoltages occurrence.

Nowadays, microgrids are expanding due to their numerous benefits. However, the control and protection of microgrids is a serious challenge. All the implemented plans for the protection of microgrids have drawbacks. This study presents a bi-level multi-agent system (MAS) approach to microgrids protection. The first level is responsible for microgrid lines protection. Firstly, it calculates the pilot impedance of each line. For line’s internal faults, pilot impedance is a limited number, but for line’s external faults, it will be infinite. so, the line’s internal fault is detected by evaluation of pilot impedance with a predetermined value. The second level is responsible for Distributed Generation (DGs) protection. Firstly, it decomposes the DGs output signals by Discrete Wavelet Transform (DWT). Then, it multiplies the summations of the first and second level’s details of each signal together as CC index. CC is zero in normal grid conditions and has a negative peak with a sharp negative rate in external faults, and will experience a positive peak with a sharp positive rate for internal faults and changes with a very slow rate in case of grid’s natural transitions. So, the agent detects the fault by evaluating the CC. The simulation results in a 5-bus microgrid indicate the proposed scheme protects the microgrid with a reliability of 100% with considering all microgrid’s uncertainties.

This paper has designed an upgraded form of the boost topology. The voltage ratio of the traditional step-up topology has been increased in quadratic form. Moreover, a low value of the duty cycle, number of components, and voltage/current stresses besides a high efficiency are bold features. The different parameters have been extracted for the ideal/non-ideal modes of the components and continuous/discontinuous current modes. In addition, the different features, such as the current/voltage stresses, have been compared. The efficiency of the designed topology has been extracted, and its various kind of power losses have been compared. The small-signal analysis has been done, and the bode diagram of the system has been extracted. Besides the increased voltage ratio of the designed topology compared to the traditional step-up converter, the continuity of the input current has remained a brilliant feature. Moreover, the semiconductors' stresses have been low-value compared to the recently proposed topologies. Moreover, higher efficiency besides higher voltage gain has been achieved. Finally, the experimental results have been compatible with the simulation and theoretical outcomes. The higher voltage gain of the proposed converter has been caused by the lower value of the duty cycle in comparison with the conventional boost converter, besides an acceptable efficiency and semiconductor stresses.

The use of Demand-Side Management (DSM) to increase the reliability of composite power systems at hierarchical level II (HLII) with Electric Vehicles (EVs) is an important issue that has not been studied so far. Studies that have been conducted assumed that EVs are connected to the power system during the mid-peak load and peak load in two charge levels with uncertainty in influence and three load shifting levels (85%, 90%, and 95%). The reliability indices Loss of Load Expectation (LOLP), Expected Energy Not Supplied (EENS), Expected Health Duration (EHDUR), and Expected Margin Duration (EMDUR) are calculated. The present paper uses Monte Carlo Simulation (MCS) in modeling the uncertainty in the generation and transmission capacity of the power system and the influence of EVs. The modeling was performed on IEEE-RBTS standard system using the MATLAB software. The result indicates that more penetration of EVs will lead to higher load levels, and thereby LOLP and EENS indices will change much more, a trend that increases even more when EVs are charged during peak load. It is possible to increase EHDUR and EMDUR values by increasing load-shifting levels (95% to 90% and 85%).

With the high penetration of DGS in the distribution network and its impact on the power loss and voltage profile of the network, the choice of location and the optimal size of the DG has become a challenge for utility companies. In this paper, a method for determining the optimal location and size of dispatchable DG at different load levels for optimal utilization of the distribution network is presented. The goal is to reduce active power losses and improve voltage profiles for stable system performance. The average daily load demand is considered as the load demand profile. The optimal location of DG is determined by sensitivity analysis based on a new voltage stability index. The voltage stability index is based on the voltage breakdown feature and provides an overview of the network voltage stability so that it can show the effect of DG installation location on network voltage stability. DG provides loads at different levels, then by selecting the appropriate bus from the most important buses in terms of index, the optimal size of DG is determined using a search algorithm and based on the lowest active power losses for different load levels. The proposed method on IEEE 33 bus network has been tested using MATLAB software, and its results have been compared with other available methods. The results show the effectiveness of the proposed method in reducing active power losses and improving the voltage profile compared to other available methods.

This paper proposes a non-invasive negative sequence impedance-based technique to detect stator turn-to-turn faults (STTFs) and dentify the related faulty phase at early stages based on the tracking the magnitude and angle variations of the negative sequence current component generated due to STTFs. To extract these indicators, a simplified steady-state negative sequence equivalent circuit of the induction motor is used. To neutralize the effect of various produced disturbances by the inherent non-ideal construction of the machine and also unbalanced feed voltage to the STTF diagnosis, they will be estimated and removed from the main obtained component. It is shown experimentally that the introduced technique is independent of mechanical loading level (load variations) and is applicable for network or inverter-fed motors as well. Online fault detection and faulty phase identification, as the most important goals of the protection plan, are accessible by defining an appropriate threshold for the magnitude and allowable range of angle variation of the introduced criterion, respectively. The performance of the method is evaluated by simulation as well as multiple experimental tests. The experimental results have shown that from the sensitivity point of view, even weak faults are detectable by such a technique. Also, the obtained tests showed that such technique is robust, reliable and secure in the face of unbalanced voltage sources and load level variations. In addition, the performance of this method for the inverter-fed mode showed that the related sensitivity will be increased in such a condition.