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Summary: The continuous increase of the distributed energy resources (DERs) penetration levels leads to voltage stability problems in the distribution system. One of the approaches for the mentioned emerging challenge is the proper placement of automatic voltage regulators (AVRs). This paper investigates the optimal placement and sizing of AVRs in a distribution network by presenting a new modification of the teaching‐learning‐based optimization (TLBO) algorithm. The objective functions consist of minimizing the distribution system voltage deviation, energy generation cost, and electrical losses. The modification improves the convergence velocity and accuracy of the TLBO algorithm using the combination of mutation technique and quasi‐opposition‐based‐learning concept. This paper compares the performance of the proposed algorithm with other famous evolutionary algorithms. The test distribution system contains installed DERs that work more efficiently after the placement of AVRs based on the mentioned objective functions by the proposed optimization algorithm. The simulation results display the best optimization algorithms for AVRs placement with a significant level of less than 0.10 (ie, probability‐value). The proposed multiobjective optimization algorithm's considerable merit is the accuracy and convergence velocity in solving this specific optimization problem. [ABSTRACT FROM AUTHOR]

Summary The power grid constructed with electric power router (EPR) will have the ability of flexibly controlling the voltage and power flow on each line of the grid, which will be helpful to maximize the integration of the renewable distributed generation to the grid. Most of the current methods for transmitting energy depend on storage unit or large scale calculation, which are relatively difficult. To avoid these disadvantages, this paper proposed a two‐step routing strategy based on the improved shortest path method for DC power grid with EPRs. The improved shortest path method combines Shortest Path Faster Algorithm (SPFA) with depth first search (DFS) algorithm, which could handle the negative weights and the negative cycle issue in the graph of the power flow paths. The increase of the transmission line power loss and the EPR's power loss are taken as the weight for the path search method to evaluate the cost of the path. Applying the proposed method to each power demand and supply finally helps to obtain the current distribution of the whole grid. By analysis of typical scenarios, compared with the power flow distribution of traditional DC power grid, the one produced by the proposed strategy could improve the power transmission capability as well as reduce the maximum voltage drop in the network. Besides, this strategy introduces less power loss, than many other ways do, in power routing. The effectiveness of the rioting strategy is related to the configuration of the network. [ABSTRACT FROM AUTHOR]

The global trends toward increasing clean and sustainable power generation have brought significant changes and developments in electrical distribution networks. The existing passive networks are being restructured to facilitate renewable distributed generations to ensure high degree of reliability of power supply to customers. A distribution system reliability assessment (DSRA) is crucial to analyze the risk and cost associated with power interruptions and take necessary preventive and corrective actions. This paper presents an approach to DSRA and carries out a comprehensive reliability assessment of an active distribution network (ADN) connected with solar, wind, and tidal energy sources. A multi‐state reliability model is developed, combining the Markov and well‐being frameworks to determine the reliability of a network energized by multiple renewable energy sources (RESs). The load point reliability and worth‐oriented indices, namely SAIDI, SAIFI, CAIDI, AENS, EENS, ECOST and IEAR, are evaluated to analyze the impacts of the three RESs on the reliability of the ADN. The paper also proposes two new metrics to estimate the benefits of adding RESs from the reliability worth and cost perspectives. The analyses have been carried out on the Roy Billinton Test System. The results show that the maximum reliability worth and cost benefits can be extracted from a combined operation of multiple RESs. A combination of solar‐wind‐tidal energy sources, therefore, can be an effective solution for countries having long coastlines to fulfill not only the sustainable energy goals but also to improve the grid's reliability and reduce the monetary losses incurred due to customer interruptions. [ABSTRACT FROM AUTHOR]

Summary: "Electric vehicles (EVs) are one of the most promising technologies to green the transportation systems. However, high penetration of EVs brings heavy electricity demand to the power grid." Due to the intermittent character of renewable energy sources (RESs), it turns out to be very challenging to manage EV charging with other renewable generation and grid load. This paper aims to introduce a dispatch strategy assisted with the optimization concept for enhancing the economy of the microgrid system. The major objective is to minimize the cost of system operation and environmental control when meeting system load requirements. The output constraints related to the distributed power supply, such as power limits, are subjected to optimization. To solve this optimization issue, a new "Fitness Sorted Moth Search algorithm (FS‐MSA)" is introduced. Finally, the proposed work is compared and validated with other existing works with respect to various measures. The enhanced outcomes prove the efficacy of the implemented FS‐MSA model. This work concentrates on EV adoption integrated with RES for sustainable mobility. On observing the result, it can be noticed that the adopted scheme was 81.97%, 82.03%, 82%, and 81.97%, better than existing genetic algorithm, particle swarm optimization (PSO), moth search algorithm, and lagrange multiplier optimization (LMO) models for mean case scenario. [ABSTRACT FROM AUTHOR]

Summary: This paper aims to advance the recently progressing research on solid‐state transformers (SST) and examines the impact of uncertainty on load demand and distributed generation (DG) units while integrating SST into an active distribution network (ADN) in the presence of battery backed solar photovoltaic (BBSPV) and wind generation. The uncertainty related to solar irradiance, wind speeds, and load demands is modeled through kernel density estimation (KDE), generalized extreme value (GEV) distribution, and Gaussian distribution summed with the maximum likelihood estimation (MLE) approach respectively. The K‐medoid clustering procedure is utilized to group the load demand into multiple load levels, which helps in the intelligent scheduling of charging and discharging of battery energy storage systems (BESS). The distribution network planning process manages two conflicting criterion functions of real power loss (RPL) reduction and sum of square deviations of the expected voltage values, which are optimized utilizing the non‐dominated sorting genetic algorithm (NSGA‐II). The probabilistic power flow uses the direct load flow procedure utilizing bus injection to branch current (BIBC) matrix along with the forward sweep method to investigate each run of Monte Carlo simulation (MCS). Multiple case studies have been conducted on the IEEE 33 bus radial distribution network (RDN). The outcomes demonstrate the potential benefits of RPL reduction and voltage profile improvement (VPI) with increasing penetration levels of SST. [ABSTRACT FROM AUTHOR]

Summary: The integration of distributed energy resources (DERs) with conventional systems emerges as an intelligent solution for providing uninterrupted and secure power even at times of high load demand. Better load management with a mature fault handling mechanism makes AC a viable option which has an efficiency of 78.24%. In contrast with less power loss and slightly better efficiency of 84.6%, DC microgrid is a reliable option in a low power environment. In order to accommodate all operating conditions and load types, a hybrid system can be designed with a theoretical efficiency of more than 90%. Bidirectional power flows, low inertia, the transition between different modes of operations are the challenges for the protection of alternating current (AC) and direct current (DC) microgrid systems. Power balance fluctuation, absence of zero‐crossing currents, selection of suitable grounding, and coordination between different rating devices restrict the hybrid system to achieve the said efficiency constantly. This paper reviews in detail of existing protection along with grid‐connected algorithms for both modes of operation. Finally, the limitation, major hurdles, and future course of action for a reliable, efficient, and secure hybrid grid system are figured out. [ABSTRACT FROM AUTHOR]

Summary: The distributed generation (DG) is getting extensively integrated in existing power distribution system because of the massive development in green energy technologies and their economical, technical, and environment benefits. However, apart from beneficial aspects, DGs also have various and complex technical limitations, major of which are loss of protection coordination among protection devices which can lead to malfunctioning of protection devices, blind protection, fuse blowing, and permanent outage of power supply due to temporary faults. In this paper, a novel curve fitting technique is designed to restore much influenced recloser‐fuse coordination using the directional properties of midline recloser for upstream and downstream protection devices coordination. It also works on fuse‐saving scheme. Using Electrical Transient Analysis Program (ETAP) Software, the proposed methodology is implemented on a real 11 kV Rajewala radial distribution feeder starting from 132 kV Eimnabad grid station, district Gujranwala, Pakistan. Present here are some key results. Different case studies are carried out and results validate the effectiveness of the proposed methodology, and the coordination among protection devices is sustained even after DGs integration in the system. [ABSTRACT FROM AUTHOR]

Summary: Increased energy demands due to rapid industrialization, environmental concerns with fossil fuel–based generation, diminishing fossil energy resources, transmission network congestion, and technical performance deterioration are the motivations behind the integration of small renewable distributed generation (DG) units and turning the existing power systems into a restructured one. Optimizing the technical benefits offered by DG placement is a well‐known challenge for distribution network operators (DNOs) for both fossil and renewable energy resource–based DGs, but renewable DG systems have several power quality (PQ) challenges associated additionally. Power quality is a very significant characteristic of renewable DG systems because today's loads are more sensitive to PQ disturbances and penetration of renewable energy as well as nonlinear loads is proliferating in distribution power networks. So the need for innovative power quality improvement (PQI) techniques becomes inevitable due to ongoing reformation in traditional distribution networks by the integration of renewable energy. This article presents a comprehensive analysis of power quality challenges with grid integration of renewable DG systems and current research status of associated mitigation techniques. Firstly, this paper puts emphasis on theoretically illustrating all the crucial power quality challenges associated with grid integration of renewable energy, and secondly, a thorough survey, of all PQI techniques introduced till date, is elaborated along with highlighting the opportunities for future research. Furthermore, all the crucial power quality issues, the impact of high penetration of renewable energy and mitigation techniques on power quality, are demonstrated also by simulating a grid integrated PV‐based DG system in MATLAB/Simulink. This article is believed to be very beneficial for academics as well as industry professionals to understand existing PQ challenges, PQI techniques, and future research directions for renewable energy technologies. [ABSTRACT FROM AUTHOR]

Summary: Renewable sources of energy are used extensively in the distribution grid to meet the need for growing electricity demand and to resolve the global heating crisis caused by traditional energy sources. They offer many advantages like better efficiency, power quality, and lower air pollution. One of the vital issues with these integrations is islanding condition arising due to the sudden disconnection of grid because of some abnormal situations; however, the distributed generation (DG) retains the power supply to the local loads. Thus, efficient detection of islanding and quick detachment of DG are vital to prevent failure of equipments, grid safety disruption, and risks to personnel safety. In this context, this article represents a comprehensive review of islanding issues and different islanding detection methods (IDMs) that provide a detailed assessment for filling the research gap and thereby highlights the various issues related to island detection. A broad classification of IDMs is established based on the conventional and modern techniques such as local (Active, Passive & Hybrid) and remote IDMs with their detailed illustrations including both intelligent and signal processing‐based IDMs. Comparison of various IDMs based on their merits, demerits, and various performance analysis including the non‐detection zone, detection time, quality factor, power quality, effect on a microgrid, implementation cost, and applicability in multi‐DG system is provided. Hence, this review will provide an insight for the new researchers interested in the area highlighting the different islanding detection techniques with their relative merits and demerits. [ABSTRACT FROM AUTHOR]