Optimal reconfiguration of capacitor based radial distribution system using chaotic quasi oppositional chemical reaction optimization

This paper develops an improved version of the chemical reaction optimization (CRO) algorithm based on the opposition-based learning (OBL) strategy named quasi-oppositional CRO (QOCRO) for optimal reconfiguration of a power system to minimize power loss of the network. Furthermore, to avoid suboptimal solutions and to increase the convergence rate, chaotic behavior is mapped with QOCRO, which results in chaotic QOCRO (CQOCRO). The reconfiguration technique can minimize power loss up to a certain level. Further power loss reduction may be accomplished by locating the capacitor in the optimal location. To investigate the performance of the proposed CQOCRO, QOCRO, and CRO approaches, they are successfully implemented on two test systems, namely 33-bus and 69-bus radial distribution systems. Moreover, the numerical results are compared with other population-based optimization techniques like krill herd (KH) algorithm, oppositional krill herd (OKH) algorithm, and fuzzy approach. The computational results reveal that CQOCRO is superior to QOCRO, CRO, and other algorithms available in the literature in this domain. Finally, a convergence graph is given to identify the convergence superiority of CQOCRO.

[1]  Hamid R. Tizhoosh,et al.  Opposition-Based Learning: A New Scheme for Machine Intelligence , 2005, International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06).

[2]  Aniruddha Bhattacharya,et al.  Chemical reaction optimisation for different economic dispatch problems , 2014 .

[3]  M. J. Rider,et al.  A mixed-integer LP model for the reconfiguration of radial electric distribution systems considering distributed generation , 2013 .

[4]  S. Jayalalitha,et al.  Multiobjective hybrid evolutionary approach for optimal planning of shunt capacitors in radial distribution systems with load models , 2017, Ain Shams Engineering Journal.

[5]  Provas Kumar Roy,et al.  Oppositional krill herd algorithm for optimal location of capacitor with reconfiguration in radial distribution system , 2016 .

[6]  J. L. Guardado,et al.  A genetic algorithm based on the edge window decoder technique to optimize power distribution systems reconfiguration , 2013 .

[7]  Almoataz Y. Abdelaziz,et al.  Ant Lion Optimization Algorithm for optimal location and sizing of renewable distributed generations , 2017 .

[8]  Victor O. K. Li,et al.  Chemical-Reaction-Inspired Metaheuristic for Optimization , 2010, IEEE Transactions on Evolutionary Computation.

[9]  Sakti Prasad Ghoshal,et al.  A novel opposition-based gravitational search algorithm for combined economic and emission dispatch problems of power systems , 2012 .

[10]  Vivekananda Mukherjee,et al.  A novel quasi-oppositional harmony search algorithm and fuzzy logic controller for frequency stabilization of an isolated hybrid power system , 2015 .

[11]  Devender Singh,et al.  Load type impact on distribution system reconfiguration , 2012 .

[12]  E. J. Oliveira,et al.  Optimal reconfiguration and capacitor allocation in radial distribution systems for energy losses minimization , 2010 .

[13]  Provas Kumar Roy,et al.  Multi-objective quasi-oppositional teaching learning based optimization for economic emission load dispatch problem , 2013 .

[14]  Provas Kumar Roy,et al.  Optimal short-term hydro-thermal scheduling using quasi-oppositional teaching learning based optimization , 2013, Eng. Appl. Artif. Intell..

[15]  Chandan Kumar Chanda,et al.  Reconfiguration of Distribution Networks based on Fuzzy Multiobjective Approach by Considering Loads of Different Types , 2013 .

[16]  M. Arun,et al.  Fuzzy based reconfiguration algorithm for voltage stability enhancement of distribution systems , 2010, Expert Syst. Appl..

[17]  Haitham Saad Mohamed Ramadan,et al.  Particle swarm optimization algorithm for capacitor allocation problem in distribution systems with wind turbine generators , 2017 .

[18]  C. Lakshminarayana,et al.  Optimal siting of capacitors in radial distribution network using Whale Optimization Algorithm , 2017 .

[19]  Erivelton G. Nepomuceno,et al.  WITHDRAWN: Adaptive chaotic maps and their application to pseudo-random numbers generation , 2019, Chaos, Solitons & Fractals: X.

[20]  P Rezaei,et al.  Distribution system efficiency improvement by reconfiguration and capacitor placement using a modified particle swarm optimization algorithm , 2010, 2010 IEEE Electrical Power & Energy Conference.

[21]  Behnam Mohammadi-Ivatloo,et al.  Application of a hybrid evolutionary algorithm on reactive power compensation problem of distribution network , 2018, Comput. Electr. Eng..

[22]  J. Jeslin Drusila Nesamalar,et al.  Optimizing renewable based generations in AC/DC microgrid system using hybrid Nelder-Mead – Cuckoo Search algorithm , 2018, Energy.

[23]  Ponnuthurai N. Suganthan,et al.  A multiobjective approach for optimal placement and sizing of distributed generators and capacitors in distribution network , 2017, Appl. Soft Comput..

[24]  Debapriya Das,et al.  Optimal placement of capacitors in radial distribution system using a Fuzzy-GA method , 2008 .

[25]  G. B. Jasmon,et al.  A novel method for loss minimization in distribution networks , 2000, DRPT2000. International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Proceedings (Cat. No.00EX382).

[26]  Shahryar Rahnamayan,et al.  Opposition-Based Differential Evolution (ODE) with Variable Jumping Rate , 2007, 2007 IEEE Symposium on Foundations of Computational Intelligence.

[27]  Luis Rouco,et al.  Reconfiguration of large-scale distribution networks for planning studies , 2012 .

[28]  T. Aruldoss Albert Victoire,et al.  A bio-geography-based algorithm for optimal siting and sizing of distributed generators with an effective power factor model , 2018, Comput. Electr. Eng..

[29]  J. Teng.  A direct approach for distribution system load flow solutions , 2003 .

[30]  Ahmed R. Abul’Wafa,et al.  Optimal capacitor allocation in radial distribution systems for loss reduction: A two stage method , 2013 .

[31]  Nadarajah Mithulananthan,et al.  AN ANALYTICAL APPROACH FOR DG ALLOCATION IN PRIMARY DISTRIBUTION NETWORK , 2006 .

[32]  Belkacem Mahdad,et al.  Optimal reconfiguration and reactive power planning based fractal search algorithm: A case study of the Algerian distribution electrical system , 2019, Engineering Science and Technology, an International Journal.

[33]  K. Muthukumar,et al.  Integrated approach of network reconfiguration with distributed generation and shunt capacitors placement for power loss minimization in radial distribution networks , 2017, Appl. Soft Comput..