Highly sensitive multifunction protection coordination scheme for improved reliability of power systems with distributed generation (PVs)

The high penetration of distribution generators (DGs), such as photovoltaic (PV), has made optimal overcurrent coordination a major concern for power protection. In the literature, the conventional single or multi‐objective function (OF) for phase overcurrent relays (OCRs) scheme faces challenges in terms of stability, sensitivity, and selectivity to handle the integration of DGs and ground fault scenarios. In this work, a new optimal OCR coordination scheme has been developed as a multifunction scheme for phase and ground events using standard and non‐standard tripping characteristics. This research introduces and validates a coordinated optimum strategy based on two new optimization approaches, the Tug of War Optimization algorithm (TWO) and the Charged System Search algorithm (CSS), to mitigate the effects of DGs on fault currents and locations across the power network. Industrial software is used to create a case study of a CIGRE power network equipped with two 10 MW PV systems, and the results of the proposed new optimum coordination scheme are compared to traditional schemes. The findings show that the proposed multifunction OCR scheme is able to reduce the tripping time of OCRs over different fault and grid operation scenarios and increase the sensitivity of the relays in islanding operation mode

The recent development of protection coordination schemes based on inverse of AC microgrid: A review

Integration of distributed generation systems and diversity of microgrid operations led to a change in the structure of the power system. Due to this conversion, new challenges have arisen when employing traditional overcurrent protection schemes. As a consequence, non‐classical protection schemes have attracted significant attention in the last few years. Engineers and scholars have proposed different non‐standard methods to increase the power protection system and ensure the highly selectivity performance. Although the non‐standard characteristics and their requirements, in general, have been outlined and analyzed in the available literature, protection coordination based on voltage current–time inverse, as a branch of non‐standard optimization methods, has not yet been thoroughly discussed, compared, or debated in detail. To close this gap, this review introduces a broad overview of recent research and developments of the voltage current–time inverse based protection coordination. Focuses on assessing the potential advantages and disadvantages of related studies and provide a classification and analysis of these studies. The future trends and some recommendations have been included in this review for improving fault detection sensitivity and coordination reliability

Finite-Time Adaptive Higher-Order SMC for the Nonlinear Five DOF Active Magnetic Bearing System

The active magnetic bearings (AMB) play an essential role in supporting the shaft of fast rotating machines and controlling the displacements in the rotors due to the deviation in the shaft. In this paper, an adaptive integral third-order sliding mode control (AITOSMC) is proposed. The controller suppresses the deviations in the rotor and rejects the system uncertainties and unknown disturbances present in the five DOF AMB system. The application of AITOSMC alleviates the problem of high-frequency switching called chattering, which would otherwise restrict the practical application of sliding mode control (SMC). Moreover, adaptive laws are also incorporated in the proposed approach for estimating the controller gains. Further, it also prevents the problem of overestimation and avoids the use of a priori assumption about the upper bound knowledge of total disturbance. The Lyapunov and homogeneity theories are exploited for the stability proof, which guarantees the finite-time convergence of closed-loop and output signals. The numerical analysis of the proposed strategy illustrates the effective performance. Furthermore, the comparative analysis with the existing control schemes demonstrates the efficacy of the proposed controller

A Comparative-Analysis-Based Multi-Criteria Assessment of On/Off-Grid-Connected Renewable Energy Systems: A Case Study

Different configurations of on/off-grid-connected hybrid renewable energy systems (HRESs) are analyzed and compared in the present research study for optimal decision making in Sub-Saharan Africa, facing the problems of electricity deficit. A multi-criteria analysis is performed for this purpose using MATLAB software for simulation. The obtained results show that the levelized cost of energy (LCOE) corresponding to 0% power supply deficit probability (PSDP) is 0.0819 USD/kWh, 0.0925 USD/kWh, 0.3979 USD/kWh, 0.3251 USD/kWh, 0.1754 USD/kWh, 0.1641 USD/kWh, 0.5385 USD/kWh, and 1.4515 USD/kWh, respectively, for the Grid-PV/Wind/Battery, Grid-PV/Battery, Grid-Wind/Battery, Grid-Wind, PV/Wind/Battery, PV/Battery, Wind/Battery, and stand-alone Wind systems. The CO2 emissions are 14,888.4 kgCO2/year, 16,916.6 kgCO2/year, 13,139.7 kgCO2/year, 6430.4 kgCO2/year, 11,439 kgCO2/year, 14,892.5 kgCO2/year, 10,252.6 kgCO2/year, and 1621.5 kgCO2/year, respectively, for the aforementioned systems. It is found that the Grid-connected PV/Wind/Battery is the most cost-effective system leading to a grid energy cost reduction of 30.89%. Hybridization of different renewable energy sources (RESs) could significantly improve the electricity cost and reduce the CO2 emissions. However, this improvement and this reduction depend on the used RES and the system configuration. On-grid-connected HRESs are more cost-effective than off-grid-connected HRES. The least polluting energy system is the stand-alone Wind system, which allows a reduction in the grid CO2 emissions by 93.66%. The sensitivity analysis has proven that the long-term investment, the decrease in the battery cost, and the decrease in the discount rate could lead to the reduction in the LCOE

Hybrid tripping characteristic-based protection coordination scheme for photovoltaic power systems

Due to the high penetration of renewable energy sources into the electrical power network, overcurrent relays coordination with highly sensitive and selective protection systems are now two of the most important power protection concerns. In this research, an optimal coordination strategy utilising a new hybrid tripping scheme based on current–voltage characteristics has been devised for overcurrent relays in a power network coupled to a photovoltaic system. This research develops and proves a new optimal coordination scheme based on two optimisation methods, the vibrating particles system and particle swarm optimisation algorithms, in consideration of the impact of renewable sources on fault characteristics. The new optimal coordination approach aims to improve the sensitivity and dependability of the protection system by reducing the tripping time of the overcurrent relays by employing a new hybrid tripping scheme. A specific case study, Conseil International des Grands Réseaux Electriques (CIGRE) distribution network connected to two photovoltaic systems is constructed and presented utilising Industrial software (namely ETAP), and the outcomes of the proposed optimal coordination scheme are compared with standard and recent characteristics from the literature. The hybrid tripping scheme and optimisation techniques are evaluated using different fault and power network model scenarios. The results show that the optimal hybrid tripping scheme provided successfully decreases the overall operating time of the overcurrent relays and increases the sensitivity of the relay during all fault scenarios. The reduction in overall time for the proposed hybrid tripping scheme was 35% compared to the literature for the scenario of a power grid with and without photovoltaic systems

Hybrid Tripping Characteristic-Based Protection Coordination Scheme for Photovoltaic Power Systems

Due to the high penetration of renewable energy sources into the electrical power network, overcurrent relays coordination with highly sensitive and selective protection systems are now two of the most important power protection concerns. In this research, an optimal coordination strategy utilising a new hybrid tripping scheme based on current–voltage characteristics has been devised for overcurrent relays in a power network coupled to a photovoltaic system. This research develops and proves a new optimal coordination scheme based on two optimisation methods, the vibrating particles system and particle swarm optimisation algorithms, in consideration of the impact of renewable sources on fault characteristics. The new optimal coordination approach aims to improve the sensitivity and dependability of the protection system by reducing the tripping time of the overcurrent relays by employing a new hybrid tripping scheme. A specific case study, Conseil International des Grands Réseaux Electriques (CIGRE) distribution network connected to two photovoltaic systems is constructed and presented utilising Industrial software (namely ETAP), and the outcomes of the proposed optimal coordination scheme are compared with standard and recent characteristics from the literature. The hybrid tripping scheme and optimisation techniques are evaluated using different fault and power network model scenarios. The results show that the optimal hybrid tripping scheme provided successfully decreases the overall operating time of the overcurrent relays and increases the sensitivity of the relay during all fault scenarios. The reduction in overall time for the proposed hybrid tripping scheme was 35% compared to the literature for the scenario of a power grid with and without photovoltaic systems

sj-docx-1-pie-10.1177_09544089221124451 - Supplemental material for Contribution to energy management of fuel cell/battery hybrid electric vehicles

Supplemental material, sj-docx-1-pie-10.1177_09544089221124451 for Contribution to energy management of fuel cell/battery hybrid electric vehicles by Insaf Yahia, Chokri Ben Salah, Abdelaziz Salah Saidi, Mohamed Faouzi Mimouni and Ali Alshahrani in Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering</p

Small-Scale Solar Photovoltaic Power Prediction for Residential Load in Saudi Arabia Using Machine Learning

Photovoltaic (PV) systems have become one of the most promising alternative energy sources, as they transform the sun’s energy into electricity. This can frequently be achieved without causing any potential harm to the environment. Although their usage in residential places and building sectors has notably increased, PV systems are regarded as unpredictable, changeable, and irregular power sources. This is because, in line with the system’s geographic region, the power output depends to a certain extent on the atmospheric environment, which can vary drastically. Therefore, artificial intelligence (AI)-based approaches are extensively employed to examine the effects of climate change on solar power. Then, the most optimal AI algorithm is used to predict the generated power. In this study, we used machine learning (ML)-based algorithms to predict the generated power of a PV system for residential buildings. Using a PV system, Pyranometers, and weather station data amassed from a station at King Khalid University, Abha (Saudi Arabia) with a residential setting, we conducted several experiments to evaluate the predictability of various well-known ML algorithms from the generated power. A backward feature-elimination technique was applied to find the most relevant set of features. Among all the ML prediction models used in the work, the deep-learning-based model provided the minimum errors with the minimum set of features (approximately seven features). When the feature set is greater than ten features, the polynomial regression model shows the best prediction, with minimal errors. Comparing all the prediction models, the highest errors were associated with the linear regression model. In general, it was observed that with a small number of features, the prediction models could minimize the generated power prediction’s mean squared error value to approximately 0.15

Highly sensitive multifunction protection coordination scheme for improved reliability of power systems with distributed generation (PVs)

Abstract The high penetration of distribution generators (DGs), such as photovoltaic (PV), has made optimal overcurrent coordination a major concern for power protection. In the literature, the conventional single or multi‐objective function (OF) for phase overcurrent relays (OCRs) scheme faces challenges in terms of stability, sensitivity, and selectivity to handle the integration of DGs and ground fault scenarios. In this work, a new optimal OCR coordination scheme has been developed as a multifunction scheme for phase and ground events using standard and non‐standard tripping characteristics. This research introduces and validates a coordinated optimum strategy based on two new optimization approaches, the Tug of War Optimization algorithm (TWO) and the Charged System Search algorithm (CSS), to mitigate the effects of DGs on fault currents and locations across the power network. Industrial software is used to create a case study of a CIGRE power network equipped with two 10 MW PV systems, and the results of the proposed new optimum coordination scheme are compared to traditional schemes. The findings show that the proposed multifunction OCR scheme is able to reduce the tripping time of OCRs over different fault and grid operation scenarios and increase the sensitivity of the relays in islanding operation mode

Advanced Coordination Method for Overcurrent Protection Relays Using New Hybrid and Dynamic Tripping Characteristics for Microgrid

Nowadays, the Overcurrent (OC) and Earth Fault (EF) relays coordination problem is one of the most complex and challenging concerns of power protection and network operators due to the high and volatile generation capacity of renewable energy sources in the grid. In this article, a new and dynamic optimal coordination scheme based on a novel hybrid tripping characteristic has been designed and developed for Over Current Relays (OCRs). Considering the impact of renewable energy sources such as the photovoltaic (PV) system on fault characteristic, this work presents and verifies a novel dynamic and hybrid tripping to achieve minimum tripping time and improve the OCR and EF relays coordination performance in terms of security, sensitivity, and selectivity. The proposed dynamic and hybrid scheme will help the OCRs to cover the EF events, and it has been tested under different fault scenarios compared to the literature. The IEEE-9 and IEEE-33 bus systems are implemented in the ETAP package to validate the effectiveness of the proposed hybrid characteristics against traditionally well-established IEC characteristics. Furthermore, the performance of the proposed advance and dynamic protection approach which doesn&#x2019;t require a communication infrastructure is investigated for a power network with PV plants under different grid operation modes and topology to provide more robustness protection system. The results, as presented using Industrial software (ETAP), showed that the novel dynamic and hybrid tripping scheme improved the speed of the total time tripping different fault scenarios and location by more than 50&#x0025; and covers all EF events compared to traditional OCR schemes from the literature. The proposed novel dynamic approach has superior performance in detecting high-impedance faults and significantly reducing the tripping time on the IEEE 33 bus network by 47&#x0025;