Optimal Coordination of DOC Relays Incorporated into a Distributed Generation-Based Micro-Grid Using a Meta-Heuristic MVO Algorithm

Abdelsalam, Mahmoud; Diab, Hatem

doi:10.3390/en12214115

Cited by 7 publications

(5 citation statements)

References 34 publications

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“…Linear programming was used to determine the optimal time multiplier setting (TMS) for these relays. Similarly, in [12], the optimal coordination of DOC relays was attained using a multi-verse optimization (MVO) algorithm, which demonstrated preeminent performance compared to the particle swarm optimization (PSO) algorithm. Recently, scholars have investigated hybrid approaches to tackle the problem of the optimal coordination of DOCRs [13][14][15][16][17].…”

Section: Literature Reviewmentioning

confidence: 99%

Improving Directional Overcurrent Relay Coordination in Distribution Networks for Optimal Operation Using Hybrid Genetic Algorithm with Sequential Quadratic Programming

Al-Bhadely,

İnan

2023

Energies

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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.

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Section: Literature Reviewmentioning

confidence: 99%

Improving Directional Overcurrent Relay Coordination in Distribution Networks for Optimal Operation Using Hybrid Genetic Algorithm with Sequential Quadratic Programming

Al-Bhadely,

İnan

2023

Energies

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“…We can always observe black holes, and they are characterized by the vast gravitational forces that make every ambient object attracted to them. The last element is called the wormhole; it has the authority to exchange objects either between different universes or between different parts of one universe [38,39].…”

Section: The Multi-verse Optimization Algorithmmentioning

confidence: 99%

“…The above method has been applied in significant optimization applications and the management of processes related to renewable energy and power systems [38,39].…”

Section: The Multi-verse Optimization Algorithmmentioning

confidence: 99%

“…where 𝑋(𝑡 + 1) is the location of the hawks in the iteration (𝑡 + 1); 𝑋 𝑟𝑎𝑏𝑏𝑖𝑡 (𝑡) is the location of the rabbit (the victim); 𝑟 1 to 𝑟 4 and 𝑞 are random numbers that can vary between 0 and 1; 𝑋 𝑟𝑎𝑛𝑑 (𝑡) represents a hawk which is chosen randomly; and 𝑋 𝑚 is the average location of the current population of hawks which can be calculated from Equation (38):…”

Section: The Harris Hawks Optimization Algorithmmentioning

confidence: 99%

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A Multi-Objective Optimal Power Flow Control of Electrical Transmission Networks Using Intelligent Meta-Heuristic Optimization Techniques

2021

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Optimal power flow (OPF) is considered one of the most critical challenges that can substantially impact the sustainable performance of power systems. Solving the OPF problem reduces three essential items: operation costs, transmission losses, and voltage drops. An intelligent controller is needed to adjust the power system’s control parameters to solve this problem optimally. However, many constraints must be considered that make the design process of the OPF algorithm exceedingly tricky due to the increased number of limitations and control variables. This paper proposes a multi-objective intelligent control technique based on three different meta-heuristic optimization algorithms: multi-verse optimization (MVO), grasshopper optimization (GOA), and Harris hawks optimization (HHO) to solve the OPF problem. The proposed control techniques were validated by applying them to the IEEE-30 bus system under different operating conditions through MATLAB simulations. The proposed techniques were then compared with the particle swarm optimization (PSO) algorithm, which is very popular in the literature studying how to solving the OPF problem. The obtained results show that the proposed methods are more effective in solving the OPF problem when compared to the commonly used PSO algorithm. The proposed HHO, in particular, shows that it can form a reliable candidate in solving power systems’ optimization problems.

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“…Authors of [23] considered different DG penetration levels with a radial type network using gravitational search algorithm (GSA). Authors of [24] used non-standard protection curves, and the curve parameters were included in the optimization problem. Even though they used a novel algorithm, the comparison was done only with particle swarm optimization (PSO).…”

Section: Literature Reviewmentioning

confidence: 99%

Optimized Adaptive Overcurrent Protection Using Hybridized Nature-Inspired Algorithm and Clustering in Microgrids

Senarathna

Hemapala

2020

Energies

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Microgrids have been popularized in the past decade because of their ability to add distributed generation into the classic distribution systems. Protection problems are among several other problems that need solutions in order to extract the full capability of these novel networks. This research follows the branches of two major solutions, namely adaptive protection and protection optimization. Adaptive protection implementation with a novel concept of clustering is considered, and protection setting optimization is done using a novel hybrid nature-inspired algorithm. Adaptive protection is utilized to cope with the topology variations, while optimization techniques are used to calculate the protection settings that provide faster fault clearances in coordination with backup protection. A modified IEEE 14 bus system is used as the test system. Validation was done for the fault clearing performance. The selected algorithm was effective than most other algorithms, and the clustering approach for adaptive overcurrent protection was able to reduce the number of relays’ setting groups.

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Optimal Coordination of DOC Relays Incorporated into a Distributed Generation-Based Micro-Grid Using a Meta-Heuristic MVO Algorithm

Cited by 7 publications

References 34 publications

Improving Directional Overcurrent Relay Coordination in Distribution Networks for Optimal Operation Using Hybrid Genetic Algorithm with Sequential Quadratic Programming

Improving Directional Overcurrent Relay Coordination in Distribution Networks for Optimal Operation Using Hybrid Genetic Algorithm with Sequential Quadratic Programming

A Multi-Objective Optimal Power Flow Control of Electrical Transmission Networks Using Intelligent Meta-Heuristic Optimization Techniques

Optimized Adaptive Overcurrent Protection Using Hybridized Nature-Inspired Algorithm and Clustering in Microgrids

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