Modified Social Group Optimization—a meta-heuristic algorithm to solve short-term hydrothermal scheduling

Naik, Anima; Satapathy, Suresh Chandra; Abraham, Ajith

doi:10.1016/j.asoc.2020.106524

Cited by 57 publications

(19 citation statements)

References 83 publications

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“…Reference [308] has solved the CSTHTS problem using a modified social group algorithm in which the acquiring phase of the original social group optimization algorithm was modified to get improved convergence behaviour. Reference [309] introduced for the first time the metaheuristic lightening attachment optimization algorithm which mathematically mimics the upward and downward leader movements of lightning arcs.…”

Section: Genetic Algorithmmentioning

confidence: 99%

Conventional and Metaheuristic Optimization Algorithms for Solving Short Term Hydrothermal Scheduling Problem: A Review

et al. 2021

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Short term hydrothermal scheduling (STHTS) is a non-linear, multi-modal and very complex constrained optimization problem which has been solved using several conventional and modern metaheuristic optimization algorithms. A number of research articles have been published addressing STHTS using different techniques. This article presents a comprehensive review of research published for solving the STHTS problem in the last four decades.INDEX TERMS Short term hydrothermal scheduling, conventional algorithms, meta-heuristic algorithms, no free lunch theorem

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Section: Genetic Algorithmmentioning

confidence: 99%

Conventional and Metaheuristic Optimization Algorithms for Solving Short Term Hydrothermal Scheduling Problem: A Review

et al. 2021

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“…The nonlinear issues established in conventional grid and issues due to integration of wind system has been overcame in Nayak et al 20 using GOA‐based cascade controller. The improvement in frequency oscillation has been established by hydrogen aqua equalizer in Nayak et al 21 Hybrid Dragonfly and Pattern Search Algorithm based 2dof‐PID approach provided in Mishra et al 22 Modified Social Group Optimization for managing issues of hydrothermal scheduling presented in Naik et al 23 Modified African buffalo optimization used for obtaining an improvement in system performance with the integration of storage devices discussed in Singh et al 24 Enhanced coyote optimizer‐based cascaded load frequency controllers are discussed in Abou El‐Ela et al 25 and multistage PID approach for frequency dynamics control approach presented in Annamraju and Nandiraju 26 for frequency stability. The life cycle of distributed energy system for microgrid system is well addressed in Ali et al 27 fractional order Type II fuzzy based controller approach is presented in Sahoo et al 28 Modified wheal optimization technique (MWOA) based approach is discussed for solving frequency regulation problem in Khadanga et al 29 …”

Section: Introductionmentioning

confidence: 99%

Performance analysis of modified sine cosine optimized multistage FOPD‐PI controller for load frequency control of an islanded microgrid system

Mishra

Prusty

Panda

2021

Int J Numerical Modelling

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This research work proposes a modified sine cosine algorithm (mSCA) to optimize the parameters of a multistage fractional‐order PD‐PI (MSFOPD‐PI) controller for load frequency control of an isolated AC microgrid. Microgrid considered here is a cluster of renewable energy sources like photovoltaic (PV), wind turbine generators (WTG) which diverges from their optimal operating point due to change in its environment. Initially, the performance of proposed mSCA algorithms is compared with the original sine cosine algorithm (CSA) well as other techniques like Crow search algorithm (CSA), Artificial bee colony (ABC), Cuckoo Search (CS), Gravitational search algorithm (GSA), Dragonfly (DA) and Genetic algorithm (GA) techniques using benchmark test functions reported in the literature. In the next stage, proposed mSCA is applied to optimize MS FOPD‐PI controller parameters under different fluctuating scenarios of source and load. To demonstrate the supremacy of the proposed MS FOPD‐PI controller the performances are compared with conventional PID, PI and I controllers. A sensitivity analysis is made by varying the system parameters to justify the controller's robustness.

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“…To solve problems of this kind, researchers use several different methods to determine the right approach for a specific problem [2,3]. Scientists are also constantly searching for more sophisticated modeling strategies [1,4,5]. The conventional exact approach should be used for smaller problems where the problems are constant and distinct [4,5].…”

Section: Introductionmentioning

confidence: 99%

“…Scientists are also constantly searching for more sophisticated modeling strategies [1,4,5]. The conventional exact approach should be used for smaller problems where the problems are constant and distinct [4,5]. The conventional exact solution approach cannot escape local optimum in real-world problems, as real-world problems are not always differentiable [6].…”

Section: Introductionmentioning

confidence: 99%

A Modified Niching Crow Search Approach to Well Placement Optimization

et al. 2021

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Well placement optimization is considered a non-convex and highly multimodal optimization problem. In this article, a modified crow search algorithm is proposed to tackle the well placement optimization problem. This article proposes modifications based on local search and niching techniques in the crow search algorithm (CSA). At first, the suggested approach is verified by experimenting with the benchmark functions. For test functions, the results of the proposed approach demonstrated a higher convergence rate and a better solution. Again, the performance of the proposed technique is evaluated with well placement optimization problem and compared with particle swarm optimization (PSO), the Gravitational Search Algorithm (GSA), and the Crow search algorithm (CSA). The outcomes of the study revealed that the niching crow search algorithm is the most efficient and effective compared to the other techniques.

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Modified Social Group Optimization—a meta-heuristic algorithm to solve short-term hydrothermal scheduling

Cited by 57 publications

References 83 publications

Conventional and Metaheuristic Optimization Algorithms for Solving Short Term Hydrothermal Scheduling Problem: A Review

Conventional and Metaheuristic Optimization Algorithms for Solving Short Term Hydrothermal Scheduling Problem: A Review

Performance analysis of modified sine cosine optimized multistage FOPD‐PI controller for load frequency control of an islanded microgrid system

A Modified Niching Crow Search Approach to Well Placement Optimization

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