Novel design of artificial ecosystem optimizer for large-scale optimal reactive power dispatch problem with application to Algerian electricity grid

Optimization of reactive power dispatch (ORPD) problem is a key factor for stable and secure operation of the electric power systems. In this paper, a newly explored nature-inspired optimization through artificial ecosystem optimization (AEO) algorithm is proposed to cope with ORPD problem in large-...

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Vydané v:Neural computing & applications Ročník 33; číslo 13; s. 7467 - 7490
Hlavní autori: Mouassa, Souhil, Jurado, Francisco, Bouktir, Tarek, Raja, Muhammad Asif Zahoor
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London Springer London 01.07.2021
Springer Nature B.V
Predmet:
Algorithms
Artificial Intelligence
Combinatorial analysis
Complexity
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Data Mining and Knowledge Discovery
Design optimization
Electric power grids
Electric power systems
Electricity distribution
Image Processing and Computer Vision
Optimization techniques
Original Article
Performance evaluation
Power dispatch
Probability and Statistics in Computer Science
Reactive power
System effectiveness
Variance analysis
Voltage stability
Real power loss
Optimal reactive power dispatch
Voltage deviation
Voltage stability index
Large-scale test system
Artificial ecosystem optimization algorithm
ISSN:0941-0643, 1433-3058
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Shrnutí:Optimization of reactive power dispatch (ORPD) problem is a key factor for stable and secure operation of the electric power systems. In this paper, a newly explored nature-inspired optimization through artificial ecosystem optimization (AEO) algorithm is proposed to cope with ORPD problem in large-scale and practical power systems. ORPD is a well-known highly complex combinatorial optimization task with nonlinear characteristics, and its complexity increases as a number of decision variables increase, which makes it hard to be solved using conventional optimization techniques. However, it can be efficiently resolved by using nature-inspired optimization algorithms. AEO algorithm is a recently invented optimizer inspired by the energy flocking behavior in a natural ecosystem including non-living elements such as sunlight, water, and air. The main merit of this optimizer is its high flexibility that leads to achieve accurate balance between exploration and exploitation abilities. Another attractive property of AEO is that it does not have specific control parameters to be adjusted. In this work, three-objective version of ORPD problem is considered involving active power losses minimization and voltage deviation and voltage stability index. The proposed optimizer was examined on medium- and large-scale IEEE test systems, including 30 bus, 118 bus, 300 bus and Algerian electricity grid DZA 114 bus (220/60 kV). The results of AEO algorithm are compared with well-known existing optimization techniques. Also, the results of comparison show that the proposed algorithm performs better than other algorithms for all examined power systems. Consequently, we confirm the effectiveness of the introducing AEO algorithm to relieve the over losses problem, enhance power system performance, and meet solutions feasibility. One-way analysis of variance (ANOVA) has been employed to evaluate the performance and consistency of the proposed AEO algorithm in solving ORPD problem.
Bibliografia:ObjectType-Article-1
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ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-020-05496-0