Multi-Objective Optimal Power Flow Solution Using a Non-Dominated Sorting Hybrid Fruit Fly-Based Artificial Bee Colony

A new optimization technique is proposed for solving optimization problems having single and multiple objectives, with objective functions such as generation cost, loss, and severity value. This algorithm was developed to satisfy the constraints, such as OPF constraints, and practical constraints, s...

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Bibliographic Details
Published in:Energies (Basel) 2022-06, Vol.15 (11), p.4063
Main Authors: Mallala, Balasubbareddy, Papana, Venkata Prasad, Sangu, Ravindra, Palle, Kowstubha, Chinthalacheruvu, Venkata Krishna Reddy
Format: Article
Language:English
Subjects:
ABC algorithm
Algorithms
Decision making
Food
Foraging behavior
Fruit flies
fruit fly algorithm
fruit fly-based ABC algorithm
Fruits
multi-objective optimization
Multiple objective analysis
Optimization algorithms
Optimization techniques
Pareto optimization
Population
Power flow
ramp rate limits
severity value
Sorting algorithms
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Summary:A new optimization technique is proposed for solving optimization problems having single and multiple objectives, with objective functions such as generation cost, loss, and severity value. This algorithm was developed to satisfy the constraints, such as OPF constraints, and practical constraints, such as ram rate limits. Single and multi-objective optimization problems were implemented with the proposed hybrid fruit fly-based artificial bee colony (HFABC) algorithm and the non-dominated sorting hybrid fruit fly-based artificial bee colony (NSHFABC) algorithm. HFABC is a hybrid model of the fruit fly and ABC algorithms. Selecting the user choice-based solution from the Pareto set by the proposed NSHFABC algorithm is performed by a fuzzy decision-based mechanism. The proposed HFABC method for single-objective optimization was analyzed using the Himmelblau test function, Booth’s test function, and IEEE 30 and IEEE 118 bus standard test systems. The proposed NSHFABC method for multi-objective optimization was analyzed using Schaffer1, Schaffer2, and Kursawe test functions, and the IEEE 30 bus test system. The obtained results of the proposed methods were compared with the existing literature.
ISSN:1996-1073
1996-1073
DOI:10.3390/en15114063