Chaotic slime mould optimization algorithm for optimal load-shedding in distribution system

Abid, Md. Shadman; Apon, Hasan Jamil; Ahmed, Ashik; Morshed, Khandaker Adil

doi:10.1016/j.asej.2021.101659

Cited by 34 publications

(12 citation statements)

References 25 publications

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“…For two scenarios, simulations are run. Scenario 1 considers various islanded modes based on existing research [15,[26][27], and a load control program is implemented. In Scenario 2, the uncertainty w.r.t.…”

Section: Resultsmentioning

confidence: 99%

“…As considered in [15,[26][27][28], the hourly variation in network loading profile and power generations are given in Fig. 5.…”

Section: Comparative Analysis With Literaturementioning

confidence: 99%

“…In [26], to balance the hourly load demand with the available DG generation under islanding conditions, a grasshopper optimization algorithm (GOA) is proposed for voltage stability guarantee with a distributed optimal amount of load shed is analysed. ischaotic slime mould algorithm (CSMA) [27] for optimal load control (OLC) for voltage stability improvement in islanded RE integrated AND. In [28], an adaptive inertia weight teaching-learning-based optimization (ATLBO) for OLC is introduced with the goal of maximising social welfare in a smart grid (SG) environment.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, adaption of meta-heuristic approaches can ensure optimal results compared to conventional approaches. The majority of the reviewed works are focused on load shed in conventional ADNs, whereas a few works [15,[26][27][28] are focused on OLC in a SG environment. In this background, the research has the following contributions.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Pelican Optimization Algorithm for Optimal Demand Response in Islanded Active Distribution Network Considering Controllable Loads

2022

IJIES

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One of the challenging tasks in an active distribution network (AND) embedded with intermittent renewable energy sources (RES) under islanding conditions is the maintenance of frequency and voltage profiles within tolerable limits. Failing to maintain these operational requirements may lead to voltage collapse or complete blackout of the network. In order to avoid this scenario, ADNs may function with contemporary load shedding schemes but these schemes may result in an inadvertent and excessive amount of load shedding, thereby consequently causing unsatisfactory and low reliability at the consumer level. Thus, this paper used Pelican optimization algorithm (POA) approach for minimising the amount of load to be shed by determining the optimal amount of load to be shed within the consumers' specified limits. Simulations are performed on IEEE 33-bus by assuming different kinds of renewable and distribution generation (DG) units. The computational efficiency of POA is compared with literature works and its performance is also characterised based on 25-indipendent runs of each case. The results obtained by POA are observed to be superior in terms of global optima and less run time. Also, the ADN is observed as satisfactory operation with fewer distribution losses, an improved voltage profile, and enhanced stability margins by imposing optimal load controls to the consumer.

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Section: Resultsmentioning

confidence: 99%

“…As considered in [15,[26][27][28], the hourly variation in network loading profile and power generations are given in Fig. 5.…”

Section: Comparative Analysis With Literaturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Pelican Optimization Algorithm for Optimal Demand Response in Islanded Active Distribution Network Considering Controllable Loads

2022

IJIES

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“…Researchers have applied the slime mould algorithm and its variants to engineering optimization problems and other research fields. For example, solving single- and du-al-objective economic and emission scheduling (EED) problems considering valve point effects [ 34 ]; determining the best operating rules for complex hydropower multi-reservoir prediction problems [ 38 ]; distributed generation (DG) solution of distribution network reconfiguration (DNR) problem [ 39 ]; photovoltaic model optimization design (Lin, 2022); demand estimation of urban water resources problem [ 40 ]; feature selection [ 41 ]; Reliability optimization of micro-milling cutting parameters [ 42 ]; Opti-mal Power Flow Problem [ 43 ]; A Cost-Effective Solution for Non-Convex Economic Load Dispatch Problems in Power Systems [ 44 ]; path planning and obstacle avoidance problem in mobile robots [ 45 ], optimal load-shedding in distribution system problem [ 30 ], etc.…”

Section: Related Workmentioning

confidence: 99%

Improved slime mould algorithm based on hybrid strategy optimization of Cauchy mutation and simulated annealing

Zhang

Liu

Bai³

2023

PLoS ONE

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In this article, an improved slime mould algorithm (SMA-CSA) is proposed for solving global optimization and the capacitated vehicle routing problem (CVRP). This improvement is based on the mixed-strategy optimization of Cauchy mutation and simulated annealing to alleviate the lack of global optimization capability of the SMA. By introducing the Cauchy mutation strategy, the optimal solution is perturbed to increase the probability of escaping from the local extreme value; in addition, the annealing strategy is introduced, and the Metropolis sampling criterion is used as the acceptance criterion to expand the global search space to enhance the exploration phase to achieve optimal solutions. The performance of the proposed SMA-CSA algorithm is evaluated using the CEC 2013 benchmark functions and the capacitated vehicle routing problem. In all experiments, SMA-CSA is compared with ten other state-of-the-art metaheuristics. The results are also analyzed by Friedman and the Wilcoxon rank-sum test. The experimental results and statistical tests demonstrate that the SMA-CSA algorithm is very competitive and often superior compared to the algorithms used in the experiments. The results of the proposed algorithm on the capacitated vehicle routing problem demonstrate its efficiency and discrete solving ability.

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Slime Mould Algorithm: A Comprehensive Survey of Its Variants and Applications

Gharehchopogh

Uçan

İbrikçi

et al. 2023

Arch Computat Methods Eng

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Meta-heuristic algorithms have a high position among academic researchers in various fields, such as science and engineering, in solving optimization problems. These algorithms can provide the most optimal solutions for optimization problems. This paper investigates a new meta-heuristic algorithm called Slime Mould algorithm (SMA) from different optimization aspects. The SMA algorithm was invented due to the fluctuating behavior of slime mold in nature. It has several new features with a unique mathematical model that uses adaptive weights to simulate the biological wave. It provides an optimal pathway for connecting food with high exploration and exploitation ability. As of 2020, many types of research based on SMA have been published in various scientific databases, including IEEE, Elsevier, Springer, Wiley, Tandfonline, MDPI, etc. In this paper, based on SMA, four areas of hybridization, progress, changes, and optimization are covered. The rate of using SMA in the mentioned areas is 15, 36, 7, and 42%, respectively. According to the findings, it can be claimed that SMA has been repeatedly used in solving optimization problems. As a result, it is anticipated that this paper will be beneficial for engineers, professionals, and academic scientists.

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Chaotic slime mould optimization algorithm for optimal load-shedding in distribution system

Cited by 34 publications

References 25 publications

Pelican Optimization Algorithm for Optimal Demand Response in Islanded Active Distribution Network Considering Controllable Loads

Pelican Optimization Algorithm for Optimal Demand Response in Islanded Active Distribution Network Considering Controllable Loads

Improved slime mould algorithm based on hybrid strategy optimization of Cauchy mutation and simulated annealing

Slime Mould Algorithm: A Comprehensive Survey of Its Variants and Applications

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