A Novel Hybrid Crow Search Arithmetic Optimization Algorithm for Solving Weighted Combined Economic Emission Dispatch with Load-Shifting Practice

The crow search arithmetic optimization algorithm (CSAOA) method is introduced in this article as a novel hybrid optimization technique. This proposed strategy is a population-based metaheuristic method inspired by crows’ food-hiding techniques and merged with a recently created simple yet robust ar...

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Bibliographic Details
Published inAlgorithms Vol. 17; no. 7; p. 313
Main Authors Dey, Bishwajit, Sharma, Gulshan, Bokoro, Pitshou N.
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.07.2024
Subjects
Algorithms
Alternative energy sources
Arithmetic
arithmetic optimization algorithm
Carbon
Carbon dioxide
combined economic emission dispatch (CEED)
Cost analysis
Costs
crow search algorithm
Demand side management
Electric vehicles
Electrical loads
Emission analysis
Energy resources
Genetic algorithms
Heuristic methods
Industrial plant emissions
Load shifting
Mathematical analysis
Optimization
Optimization algorithms
Optimization techniques
Power plants
Real time
Renewable resources
Robustness
Solar energy
Statistical analysis
Sulfur dioxide
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Summary:The crow search arithmetic optimization algorithm (CSAOA) method is introduced in this article as a novel hybrid optimization technique. This proposed strategy is a population-based metaheuristic method inspired by crows’ food-hiding techniques and merged with a recently created simple yet robust arithmetic optimization algorithm (AOA). The proposed method’s performance and superiority over other existing methods is evaluated using six benchmark functions that are unimodal and multimodal in nature, and real-time optimization problems related to power systems, such as the weighted dynamic economic emission dispatch (DEED) problem. A load-shifting mechanism is also implemented, which reduces the system’s generation cost even further. An extensive technical study is carried out to compare the weighted DEED to the penalty factor-based DEED and arrive at a superior compromise option. The effects of CO2, SO2, and NOx are studied independently to determine their impact on system emissions. In addition, the weights are modified from 0.1 to 0.9, and the effects on generating cost and emission are investigated. Nonparametric statistical analysis asserts that the proposed CSAOA is superior and robust.
ISSN:1999-4893
1999-4893
DOI:10.3390/a17070313