Differential Evolution with Parameter Adaptation Strategy to Economic Dispatch Incorporating Wind

Venkatakrishnan, G. R.; Mahadevan, J.; Rengaraj, R.

doi:10.1007/978-981-10-4852-4_14

Cited by 5 publications

(3 citation statements)

References 17 publications

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“…The Real Power Economic Dispatch (RPED) relates to allocating optimal power generation towards thermal units without violating constraints within the system. The RPED is considered as a non-linear problem [24]. In [24], the GWO algorithm was implemented and employed to solve the RPED, whilst examining the algorithms' effectiveness, robustness and feasibility.…”

Section: Overview Of Metaheuristicsmentioning

confidence: 99%

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A Comparative Study of Metaheuristics for Blood Assignment Problem

Govender

Ezugwu

2018

Proceedings of the 2018 International Conference on Algorithms, Computing and Artificial Intelligence

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Prinolan Govender School of Mathematics, Statistics and Computer ScienceMaster of Computer ScienceThe Blood Assignment Problem (BAP) is a real world and NP-hard combinatorial optimization problem. The study of BAP is significant due to the continuous demand for blood transfusion during medical emergencies. However, the formulation of this problem faces various challenges that stretch from managing critical blood shortages, limited shelf life and, blood type incompatibility that constrain the random transfusion of blood to patients.The transfusion of incompatible blood types between patient and donor can lead to adverse side effects on the patients. Usually, the sudden need for blood units arises as a result of unforeseen trauma that requires urgent medical attention. This condition can interrupt the supply of blood units and may result in the blood bank importing additional blood products from external sources, thereby increasing its running cost and other risk factors associated with blood transfusion. This however, might have serious consequences in terms of medical emergency, running cost and supply of blood units. Therefore, by taking these factors into consideration the aforementioned study implemented five global metaheuristic optimization algorithms to solve the BAP. Each of these algorithms was hybridized with a sustainable blood assignment policy that relates to the South Africa blood banks. The objective of this study was to minimize blood product wastage with emphasis on expiry and reduction in the amount of importation from external sources. Extensive computational experiments were conducted over a total of six different datasets, and the results validate the reliability and effectiveness of each of the proposed algorithms. Results were analysed across three major aspects, namely, the average levels of importation, expiry across a finite time period and computational time experienced by each of the metaheuristic algorithms. The numerical results obtained show that the Particle Swarm Optimization algorithm was better in terms of computational time. Furthermore, none of the algorithms experienced any form of expiry within the allotted time frame. Moreover, the results also revealed that the Symbiotic Organism Search algorithm produced the lowest average result for importation; therefore, it was considered the most reliable and proficient algorithm for the BAP.

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Section: Overview Of Metaheuristicsmentioning

confidence: 99%

“…The RPED is considered as a non-linear problem [24]. In [24], the GWO algorithm was implemented and employed to solve the RPED, whilst examining the algorithms' effectiveness, robustness and feasibility. The tests were conducted with different kinds of constraints with results achieving minimum fuel expenditure.…”

Section: Overview Of Metaheuristicsmentioning

confidence: 99%

A Comparative Study of Metaheuristics for Blood Assignment Problem

Govender

Ezugwu

2018

Proceedings of the 2018 International Conference on Algorithms, Computing and Artificial Intelligence

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“…The DE algorithm has been implemented to a standard IEEE 30 system with 6 thermal plants and 2 wind farms [12]. In [13][14][15][16][17][18][19][20][21], DE algorithm is used to optimize the parameters in different power system problems. But the success of DE algorithm depends on the choice of parameters like population size np, mutation rate Fand crossover rate CRvaries its performance (searching accuracy and convergence speed).…”

Section: Introductionmentioning

confidence: 99%

Implementation of Modified Differential Evolution Algorithm for Hybrid Renewable Energy System

Venkatakrishnan¹,

Rengaraj²,

Sathish³

et al. 2021

J. Nig. Soc. Phys. Sci.

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A hybrid renewable energy system, which could provide a reliable energy alternative for conventional Battery systems is implemented in this paper. The primary requirement is that the hybrid energy system should be cost-effective while meeting the energy demand. The hybrid system is implemented to a area located in Uttarakhand, India using solar photovoltaic cells to supply power during hot and humid conditions and using wind turbine generators to supply power during windy conditions. The wind turbine generators and photovoltaic cells are used in a combined manner along with the diesel generators as in case if it fails to meet the demand. In order to meet the requirements, modified Differential Evolution (DE) Algorithm is being implemented. Moreover, the effectiveness of the performance is evaluated by comparing the results obtained from modified DE with other optimization algorithms. In comparison with other optimization algorithms, results indicate that the implementation of the modified DE algorithm helps in obtaining the best cost effective solution for the system along with meeting the energy demand.

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Multi-objective optimization design of a compliant microgripper based on hybrid teaching learning-based optimization algorithm

Dao

Chau

et al. 2018

Microsyst Technol

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Differential Evolution with Parameter Adaptation Strategy to Economic Dispatch Incorporating Wind

Cited by 5 publications

References 17 publications

A Comparative Study of Metaheuristics for Blood Assignment Problem

A Comparative Study of Metaheuristics for Blood Assignment Problem

Implementation of Modified Differential Evolution Algorithm for Hybrid Renewable Energy System

Multi-objective optimization design of a compliant microgripper based on hybrid teaching learning-based optimization algorithm

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