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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Published in:	Neural computing & applications Vol. 33; no. 13; pp. 7467 - 7490
Main Authors:	Mouassa, Souhil, Jurado, Francisco, Bouktir, Tarek, Raja, Muhammad Asif Zahoor
Format:	Journal Article
Language:	English
Published:	London Springer London 01.07.2021 Springer Nature B.V
Subjects:	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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Abstract	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.
AbstractList	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. 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.
Author	Jurado, Francisco Raja, Muhammad Asif Zahoor Mouassa, Souhil Bouktir, Tarek
Author_xml	– sequence: 1 givenname: Souhil orcidid: 0000-0001-7812-8184 surname: Mouassa fullname: Mouassa, Souhil email: souhil.mouassa@univ-bouira.dz organization: Department of Electrical Engineering, University of Jaén, Department of Electrical Engineering, University of Bouira, Department of Electrical Engineering, University of Farhat Abbas, Sétif 1 – sequence: 2 givenname: Francisco surname: Jurado fullname: Jurado, Francisco organization: Department of Electrical Engineering, University of Jaén – sequence: 3 givenname: Tarek surname: Bouktir fullname: Bouktir, Tarek organization: Department of Electrical Engineering, University of Bouira – sequence: 4 givenname: Muhammad Asif Zahoor surname: Raja fullname: Raja, Muhammad Asif Zahoor organization: Future Technology Research Center, National Yunlin University of Science and Technology, Department of Electrical and Computer Engineering, COMSATS University Islamabad
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Keywords	Real power loss Optimal reactive power dispatch Voltage deviation Voltage stability index Large-scale test system Artificial ecosystem optimization algorithm
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SubjectTerms	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
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Title	Novel design of artificial ecosystem optimizer for large-scale optimal reactive power dispatch problem with application to Algerian electricity grid
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