INTERNATIONAL JOURNAL OF RESEARCH AND TECHNOLOGY IN ELECTRICAL INDUSTRY
Year:2023 | Volume:2 | Issue:2|Papers Count:12

Considering the sensitivity of high voltage direct current transmission system protection and the difficulty in identifying external DC faults, this paper presents two methods for fault detection and classification in VSC-HVDC transmission lines. These studied methods are evaluated in terms of efficiency and accuracy. This research is focused on DC faults at different distances along the lines. DC line current and voltage are selected as input to wavelet transform, and in the next step, unique and valuable features of each signal are extracted with modern signal processing methods, and then these features are used as input data for algorithms to detection and classification faults. Deep Neural Network (DNN)  and Support Vector Machine (SVM) have been investigated to detect and classify faults. In the next step, the efficiency of these algorithms was investigated and analyzed in noise conditions. The innovation of this research is replacing a new method of extracting features from the fractal dimension, which has been used to study more prominent features, and improve performance with a small number of study data and considering different conditions, and using the new feature extraction method and improving the performance of the algorithms, 96% accuracy has been achieved.

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.

Coordination between protection devices is one of the important issues in any protection scheme of an electrical power system. The tendency to increasingly use distributed generation has jeopardized the selectivity of overcurrent relays in active distribution networks. To increase the penetration level of distributed generation in these networks, an increase in the Protection Coordination Index (PCI) of the network is a must. For this purpose, in this paper, voltage-current-time characteristics and Dual Setting Directional Overcurrent Relays are used. In this case, coordination is not a trivial task and imposes further complexity. Since Dual Setting Directional Overcurrent Relays are capable to break current in both directions with separate tuning, they have the flexibility to improve the protection coordination index. Moreover, voltage-current-time characteristics employ voltage in the operation of relays. This capability can also be used in reducing the optimization of the protection scheme and provides more flexibility in coordination procedures. Afterward, the protection scheme is developed by user-adjustable voltage-current-time characteristics to improve the PCI as much as possible. The proposed scheme is modeled as a nonlinear programming approach which is solved by a Genetic Algorithm (GA).

The idea of this paper is to provide a framework for simultaneous energy cost optimization and congestion management by using shared energy storage. As a case study, this paper addresses this aim by proposing the integration of a community energy storage (CES) within a distribution system, connected to four microgrids (MGs). The shared storage system enables the MGs to reduce their energy costs by optimizing the operation of the battery using a Heuristic optimization algorithm, specifically the Teaching-Learning-Based Optimization (TLBO) algorithm. Simultaneously, the distribution system operator (DSO) leverages the shared storage to alleviate congestion by purchasing charged power from the storage manager. Interestingly, the DSO is willing to pay a premium price for the charged power from the shared storage, surpassing the prevailing electricity price during congested hours. Moreover, to account for uncertainties arising from load variations and intermittent renewable energy resources (RES), Monte Carlo simulation is employed in this study. Through comprehensive simulations and analyses, the proposed approach demonstrates the potential of CES as an effective tool for congestion relief and operational cost optimization in distribution systems, and providing economic benefits to both the MGs and the DSO.

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.

The protection of transmission and sub-transmission lines is conducted by overcurrent, line differential and distance protections among which the use of distance protection is very common.Mal-operation of protection equipment, including distance protection, can occur due to improper choose of the setting. This paper presents the proper method for calculation of the phase-to-phase loop resistance reach of distance protection with Quad characteristic and the impedance starter at the sub-transmission level to prevent mal-operation of the distance relay when processing its algorithm. In this work, based on the practical experiences on several industrial distance relays, it is shown that there is a possibility of improper detection of the fault loop by distance protection and then improper relay operation for out of zone faults. After review of the subject, and expressing the mathematical relations governing the problem, the appropriate phase-to-phase loop resistance reach determination method is put forward. Finally, using the information obtained from a practical incident, the efficiency of the proposed method is verified.

Power transformers are one of the main components of the power grids. Several main and back up protection relays are provided to protect them against different fault types. Restricted Earth Fault (REF) protection relay is used as main protection to protect transformer against in-zone phase-to-ground faults. This protection has high accuracy to detect earth faults inside the transformer protection zone. Operational experiences show that in some cases and during external high current out-zone faults which leads to current transformers (CTs) core saturation, REF relay operates incorrectly and cause unwanted trip. Relay setting base and operation curve methods to solve the problem have been devised, but the problem has not yet been completely solved. In this article, different fault types such as symmetric/asymmetric, single/multiple phases, low/high current are simulated. Then, causes of REF protection maloperation and commercial relays settings and curves are studied. The optimal setting for the relay is extracted and its effectiveness in different fault types validated by simulating real data with PSCAD and MATLAB software.

In this paper prediction error measurement (PEM) method is used for online synchronous generator parameters estimation. Unlike the usual off-line standard methods, in the proposed method instead of removing the automatic voltage regulator (AVR) from the circuit and manually disturbing the excitation voltage, a change in the reference signal of the AVR is applied and the parameters are estimated for the AVR-generator interconnected system. To adapt this modeling to real conditions, the input and output signals are mixed with noise. Since the direct application of the PEM method on noisy signals will cause a significant estimation error, the wavelet transform is used as a signal-denoising tool. Using Matlab/Simulink, synchronous generator parameters are estimated under colored noise and white noise conditions. To validate the estimated parameters, the results compare with the standard standstill frequency response (SSFR) test that was applied to the Shahid Rajaee power plant. Moreover, a three-phase short circuit to earth for a period of 2.5 cycles at the generator terminal is simulated and analyzed. The results indicate the proper accuracy of the proposed parameter estimation.

The non-dispatchable and intermittent nature of renewable distributed generators, i.e., photovoltaic and wind power plants, can lead to voltage variations and disruption in energy exchanges, especially in multi-area active distribution networks. Therefore, to manage inter-area energy exchanges in the presence of high penetration level of renewable distributed generators, the flexibility and controllability of the grid should be increased by using soft open points. However, the investment cost of soft open points is very high. On the other hand, soft open points affect the energy transactions in the multi-area active distribution network, so, they should be optimally allocated with the satisfaction of all the network areas. In this research, for the first time, a new decentralized framework for optimal siting and sizing of soft open points is developed, considering the self-interested nature of the areas and preserves their autonomy and information privacy. By using the suggested framework, different areas can negotiate with each other on the location and size of soft open points, and the relatively equal share of their investment costs. The correctness of the proposed decentralized planning model is confirmed by two case studies in MATLAB. The results confirm that the proposed method can allocate the share of each area based on the profit from new SOPs and also preserve the privacy, in both case studies.

Sectionalizing switches (SS) and lines play an essential role in improving the performance of the distribution automation system as well as reducing the outage duration of power grid customers. The operation of the sectionalizing switches and whether the lines are energized or de-energized are also dependent on each other. Considering the structural complexities related to the mathematical modelling of such problems, optimizing the planning and performance of switches and lines usually requires the use of heuristic and meta-heuristic approaches or oversimplification of network complex topology. To deal with such issues, this research presents an efficient computational model for reliability-based simultaneous switching in distribution networks with complex topologies using binary teaching learning-based optimization (BTLBO) algorithm. The performance of proposed model is demonstrated on the IEEE 123-bus system. The results show that the proposed model is effective for placement of sectionalizing switches to enhance power system reliability.

Power transformers used in the subtransmission substations of the Iranian power grid have YNd connection. In addition, a grounding transformer with YNd connection is used to create an artificial neutral on the medium voltage side. The phase to ground capacitor may have a high value in the medium voltage network. In some conditions, such as interruption of the phase-to-ground fault current in one of the output feeders, a kind of resonance is created in the network that not only damages the grounding transformer but also causes protection problems related to the misalignment of ground fault relays. In this paper, the resonance between the grounding transformer and the phase-to-ground capacitor of the medium voltage output feeders of a sample subtransmission substation is investigated, considering that the phase-to-ground fault is interrupted. In this regard, based on available currents and voltages, several indicators are defined to adjust the surge arrester and other elements of the subtransmission network. In addition, appropriate solutions are presented in order to damp the aforementioned resonance and avoid unwanted challenges.

With the increasing demand for electricity demand, power distribution utilities must provide an efficient and appropriate Service Restoration (SR) strategy to restore customers as soon as possible after power outages to increase the network resiliency and reliability. The heuristic SR algorithm presented in this article is a bi-stage algorithm that initially re-energizes some loads quickly by remote-controlled switches in the first stage and then proceeds to restore the rest of the network in the second stage. Beside solving the restoration problem in a bi-stage algorithm, determining the optimal Switching Sequences (SSs) and applying the Expected Energy Not Supplied (EENS) as objective function included in this research. Also, taking into account the time of occurrence of the failure and the daily load curve, the position of the maintenance team, load transfer capability and the traffic conditions of the network has increased the attractiveness and practicality of the proposed method. The heuristic SR algorithm was applied on a standard IEEE 69-bus system in various scenarios. The results indicated a significant difference in the solutions of the problem and the ENS in different scenarios. Finally, it was found that using this heuristic method would lead to optimal, accurate, and applicable solutions for SR in distribution networks.