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To ensure a safe and trustworthy pattern in contradiction to the possible faults, a precise, reliable, and fast relaying strategy is of high importance in an electrical power system. These challenges give the impression of being more refined in multi-loop distribution systems. More recently, overcurrent relays (OCRs) have evolved as proficient coun...
Citations
... DOPRs coordination problem under scattered generation penetration is addressed in [20]. Some natureinspired algorithms, such as Imperialistic Competition Algorithm (ICA) [21], teaching learning-based optimization (TLBO) [22], Group Search Optimization (GSO) [23], Improved Group Search Optimization (IGSO) [23], gray wolf optimization (GWO) [24], whale optimization (WWO) [25], root tree algorithm (RTA) [26], Analytic Process (AP) [27], and Harmony Search (HS) [28], Backtracking Search Algorithm (BSA) [29], Gravitational Search Algorithm (GSA) [30], modified electromagnetic field optimization [31], Jaya Algorithm (JA) [32], Hybrid Improved Invasive Weed Optimization (HIIWO) [33] are used to solve the coordination problem of DOPRs. These optimization techniques took more computational time for the exploration of the search space and exploitation of the best solutions. ...
In order to minimize or maximize an objective function, electrical engineering problems might benefit from optimization methodologies inspired by nature. This study employs a hybrid particle swarm optimizer (HPSO) to get rid of local optimum solutions and find the best global one for directional overcurrent protection relays (DOPR) protection. DOPR coordination is a highly constrained, mixed-integral nonlinear optimization problem. An adaptive defense method has been created to counteract the intentionally challenging design. Therefore, design variables such as time multiplier setting (TMS) and plug setting (PS) are utilized for each relay in the circuit. The goal function is to reduce the amount of time spent to trace the fault by all the relays. Reducing the time required for each relay to trace the fault is the aim of function. After analyzing and comparing two test studies of the IEEE benchmark using various optimization strategies, we found that the results for the IEEE 15-bus system has minimum time of 8.9 s, which is improved by 22.92% to 82.89%, and those for the IEEE 30-bus system minimum time of 22.45 s that is improved by 4.41% to 39.6%. In terms of overall DOPR operation and computational time needed to get the global optimum solution, the acquired results are demonstrably superior to those obtained using conventional and state-of-the-art methods.
... Different versions of nature-inspired optimization, such as JAYA and whale optimization, were used by the authors of [6][7][8][9] in order to address the DOCR coordination issue that was present inside the electrical power network. The DOCR design created in [10,11] was the most optimal one in terms of the physical and logical changes that were made to the layout of the system. ...
The proper coordination of directional overcurrent relays (DOCRs) is crucial in electrical power systems. The coordination of DOCRs in a multi-loop power system is expressed as an optimization problem. The aim of this study focuses on improving the protection system’s performance by minimizing the total operating time of DOCRs via effective coordination with main and backup DOCRs while keeping the coordination constraints within allowable limits. The coordination problem of DOCRs is solved by developing a new application strategy called Fractional Order Derivative Moth Flame Optimizer (FODMFO). This approach involves incorporating the ideas of fractional calculus (FC) into the mathematical model of the conventional moth flame algorithm to improve the characteristics of the optimizer. The FODMFO approach is then tested on the coordination problem of DOCRs in standard power systems, specifically the IEEE 3, 8, and 15 bus systems as well as in 11 benchmark functions including uni- and multimodal functions. The results obtained from the proposed method, as well as its comparison with other recently developed algorithms, demonstrate that the combination of FOD and MFO improves the overall efficiency of the optimizer by utilizing the individual strengths of these tools and identifying the globally optimal solution and minimize the total operating time of DOCRs up to an optimal value. The reliability, strength, and dependability of FODMFO are supported by a thorough statistics study using the box-plot, histograms, empirical cumulative distribution function demonstrations, and the minimal fitness evolution seen in each distinct simulation. Based on these data, it is evident that FODMFO outperforms other modern nature-inspired and conventional algorithms.
... This was mainly due to the substantial number of iterations required to identify suitable relay settings [3]. The optimization of coordinating OCRs in distribution networks with both single-loop and multi-loop structures has been regarded as a matter of optimization [4]. Various optimization techniques, including both conventional methods and heuristic approaches, have been utilized to calculate the optimal time dial and pick-up current settings for the DOCRs. ...
... By utilizing (3) [4][5][6] , it is possible to ascertain the maximum and minimum values for a relay's time-multiplier setting, represented as TMS i,min and TMS i,max , respectively. The specified values for these variables are 0.01 and 1.1 s, respectively. ...
In recent years, with the growing popularity of smart microgrids in distribution networks, the effective coordination of directional overcurrent relays (DOCRs) has presented a significant challenge for power system operators due to the intricate and nonlinear nature of their optimization model. Hence, this study proposes a hybrid GA-SQP algorithm to enhance the coordination of directional overcurrent relays (DOCRs) in radial and non-radial interconnected distributed power networks. The proposed approach combines the advantages of both the genetic algorithm (GA) and sequential quadratic programming (SQP) methods to optimize the objective function of relay coordination in the best manner. Thus, the proposed hybrid techniques improved the convergence of the problem and increased the likelihood of obtaining a globally optimal solution. Finally, to validate the effectiveness of the proposed algorithm, it was tested through three case studies involving the IEEE 3-Bus, 8-Bus, and modified 30-Bus distribution networks. In addition, the results were compared to those obtained using previous methods. The results obtained from the comparison of the proposed method and recent advanced research indicate that the proposed optimization approach is preeminent in terms of accuracy and total operating time as well as the continuity of the minimum margin time requirements between the primary/backup relay pairs.
... The technique is very affective in finding the global optimum values with robustness and better convergence as compared to other state of the art algorithms. In [34], JAYA algorithm is applied to solve the optimal coordination problems of OCRs in single and multi-loop distribution networks with the advantages of converging to the global optimum values with less number of iterations and computational time. In [35], the optimal coordination problems of DOCRS is solved using the whale optimization algorithm (WOA). ...
The deterministic directional overcurrent relay (DOCR) coordination approaches find limitation in providing fast and reliable protection to today’s distribution networks due to growing integration of distributed generations (DGs). In this paper, an adaptive DOCR protection coordination scheme is proposed using an efficient optimization algorithm called the dragonfly algorithm (DA). The main inspiration of the proposed DA optimization technique originates from static and dynamic swarming behaviours of dragonflies. In this approach, the dominant changes in the network topologies are identified by monitoring the status of the circuit breakers connected at the terminals of the DGs and other main power components. When any dominant changes in the network topologies or operating modes are identified, the fault current for that particular condition is calculated and the new optimal DOCRs settings for the prevailing condition are obtained from the substation central computer in online mode. The comparative results with the existing approaches justify the superiority of the proposed scheme in achieving the minimum overall relay operating time and maintaining the coordination between the primary and backup relay pairs. In the proposed adaptive protection scheme, the average percentage reduction in the overall operating times of DOCRs in the 6-bus and the IEEE 14-bus test systems with different levels DG penetration is found to be 49.7% and 15%, respectively, compared to the existing approaches.
... The learning factor and acceleration coefficient are employed for the initialization of other optimization approaches because they call for a scaling factor and crossover elements. So far as ignoring the effort of altering constraints and shortening the time needed for the optimization process are concerned, the JA and A-JA computation has a crucial advantage [35]. The goal of this work is to improve the algorithm for solving DTCTP. ...
This paper proposes a novel algorithm to optimize the discrete time-cost trade-off problem (DTCTP) in construction projects. As DTCTP is assumed NP-hard, the new metaheuristic models are investigated to contribute for decision-making of project managers. DTCTP can be modelled as multi-mode to represent real-life problems more practical. According to the model, the project activities have at least two or more durations and cost alternative modes. For solving this problem effectively, a novel optimization metaheuristic method named Advanced Jaya Algorithm (A-JA) is proposed, which is generated from Jaya Algorithm (JA). The benchmark function tests are applied to verify the model with other well-known metaheuristic methods. The key weakness of the base algorithm JA is that, it has unstable solution accuracy and low likelihood of escaping local optimums. According to the results, A-JA considerably improves these areas. Two case studies of DTCTP are carried out after verification to demonstrate the effectiveness and efficiency of the proposed algorithm in comparison with JA and three well-known methods. The results of A-JA are found to be more powerful than the base algorithm JA and the benchmark algorithms. The proposed method achieves the Pareto fronts to help decision makers to make trade-off between the objectives and choose the optimum solution considering on their preference.
... The JA is used to solve node localization problems because it is a parameter-free and less complex algorithm. It also provides better results in other fields like power maximization [28], single and multi-loop distribution systems [29] etc. ...
In wireless sensor networks (WSNs) and large-scale IoT applications, node localization is a challenging process to identify the location of the target or unknown nodes for accurate information transmission between sensor nodes. Due to their ease of hardware implementation and suitability for large-scale WSNs, range-free localization techniques have been shown in previous studies. The existing range-free localization algorithms did not consider the anisotropy factors typically seen in WSNs, leading to poor positioning accuracy. We proposed a range-free localization solution that combines the benefits of geometric constraint and hop progress-based approaches to address this issue. Each unknown node categorizes the anchor node pairs into one of three proposed categories, and the discriminating conditions are designed using the geometric information provided by the combination of the anchor node pairs and unknown nodes. A node localization algorithm is proposed to determine the position of target nodes or unknown nodes and to reduce the effect of anisotropic factors in isotropic, O-shaped, and S-shaped anisotropic WSNs using the parameter-less Jaya algorithm (JA) and range-free method of reliable anchor pair (RAP) selection approach. In the case of anisotropic WSNs (AWSNs), finding the location of target nodes is more complicated. The presented work is compared with the existing node localization methods, including Distance Vector (DV)-maxHop, Particle Swarm Optimization (PSO), and Quantized Salp Swarm Algorithm (QSSA) based localization algorithms. The proposed approach provides improved localization accuracy compared to the existing node localization methods regarding the number of anchor nodes and node density. The proposed algorithm also looks at how the degree of irregularity and computation time affect the performance.
... solve a variety of engineering challenges [30,31], and its principle is explained in the flowchart (Fig. 4). Let the objective function (x) be minimized or maximized according to the problem. ...
This article offers an efficient isosceles layout model for node deployment, and a parameter-less Jaya algorithm is also proposed as a solution to the sensor node localization issue in wireless sensor networks (WSNs). The proposed method bases its range measuring on the receive signal strength indicator (RSSI) method. The proposed layout ensures that target nodes are always within the anchor nodes’ transmission range, reducing the influence of RSSI interference and improving node localization accuracy. Compared to the earlier proposed square and equilateral layout models, the proposed model shows significant improvement. The performance of the earlier layout models and the proposed isosceles layout model for node localization is analyzed using a Jaya algorithm and compared with particle swarm optimization (PSO) and salp swarm algorithm (SSA)-based node localization algorithm. The proposed algorithm’s performance is evaluated using scalability and localization accuracy assessments. We investigate the influence of the degree of irregularity on localization accuracy for each layout. The proposed isosceles layout performs 14.16% and 8.56% better than the square and equilateral layout models for the proposed Jaya-based node localization algorithm. The proposed algorithm performs 7.16% and 4.24% better than the PSO- and SSA-based node localization algorithms for the isosceles layout model in WSNs for the same parameters. MATLAB simulation evaluates the proposed layout model and node localization algorithm.
... An improved algorithm for AC impedance extraction was used in [5]. Hybridization of particle swam optimization (HPSO) [6], grey wolf optimization [7], Marine Predator Algorithm [8], Harris Hawk Optimization (HHO) [9], jaya algorithm [10][11], whale optimization [12][13], and root tree algorithm [14] are utilised for optimum DOPR coordination and settings. A bio-inspired rooted tree algorithm [15] for optimal coordination of overcurrent relays. ...
... The JAYA algorithm, with the primary goal of avoiding the worst outcome, was initially envisioned by Rao [26][27][28]. It is an algorithm-specific parameter-less method. ...
... This inclination represents the Sanskrit word JAYA, which symbolizes triumph [29]. Figure 2 depicts the flow diagram of the Jaya algorithm [26][27][28][29][30]. ...
... Flow chart of JAYA algorithm[26][27][28][29][30]. ...
In this study, the hardness and surface roughness of selective laser-melted parts have been evaluated by considering a wide variety of input parameters. The Invar-36 has been considered a workpiece material that is mainly used in the aerospace industry for making parts as well as widely used in bimetallic thermostats. It is the mechanical properties and metallurgical properties of parts that drive the final product's quality in today's competitive marketplace. The study aims to examine how laser power, scanning speed, and orientation influence fabricated specimens. Using ANOVA, the established models were tested and the parameters were evaluated for their significance in predicting response. In the next step, the fuzzy-based JAYA algorithm has been implemented to determine which parameter is optimal in the proposed study. In addition, the optimal parametric combination obtained by the JAYA algorithm was compared with the optimal parametric combination obtained by TLBO and genetic algorithm (GA) to establish the effectiveness of the JAYA algorithm. Based on the results, an orientation of 90°, 136 KW of laser power, and 650 mm/s scanning speed were found to be the best combination of process parameters for generating the desired hardness and roughness for the Invar-36 material.
... e algorithm attempts to achieve victory by achieving accomplishments which are used for discovering an optimal solution. e Jaya optimisation algorithm has been applied to solve distribution systems [11], optimisation of thermal devices [12], solve linear power systems to an interconnection [13], and economic load dispatch optimisation problems [14]. e objective of this study is to find the feed among forage and browse legumes that gives the maximum profit to a smallholder dairy farmer. ...
Livestock feed mix or feed choice decision-making is encountered by farmers in their daily operations. Livestock feed choice and mixing is emerging as a key research area considering the impact of climate change and emergence of new technology. Smallholder dairy farmers are usually capital constrained and hence a need to investigate cost-effective feed choice that maximises profit. A study to investigate the cost-effective feed among forage and browse legumes was conducted among smallholder dairy farmers in Zimbabwe. An optimisation problem was formulated with the objective of maximising profit by selecting the most cost-effective feed among forage and browse legumes. Secondary data are used to solve the optimisation problem by implementing the Jaya optimisation algorithm. Results show that grain crop silage is the best feed choice resulting in a maximum profit of $ 66.00 per day per farmer. Further research can be directed towards investigating the effect of combining the next best feed, quality hay, and grain crop silage for profit contribution.
