A New Model for Reconfiguration and Distributed Generation Allocation in Distribution Network Considering Power Quality Indices and Network Losses

This article proposed a new model for reconfiguration and distributed generation (DG) allocation in the distribution network by considering network loss reduction and power quality improvement. The objective function aims to minimize losses and improve power quality indices by using the new antlion optimizer (ALO) algorithm. The proposed reconfiguration has been investigated on an unbalanced IEEE 33-bus grid with and without DG resources and capacitors. In this study, a branch exchange technique with an optimization method is used to determine the best network arrangement. Simulation results are implemented in different scenarios. In each of the scenarios, power quality indices and network losses before and after the optimization are compared. The results indicate that by using the proposed method, the rate of power quality indices and the losses in the case study are reduced. Also, the results of this study were compared with the results of sample studies. The results show that ALO has better performance with the goal of power loss reduction.

[1]  Seyed Mohammad Mirjalili,et al.  The Ant Lion Optimizer , 2015, Adv. Eng. Softw..

[2]  K. Ravindra,et al.  Power Loss Minimization in Distribution System Using Network Reconfiguration in the Presence of Distributed Generation , 2013, IEEE Transactions on Power Systems.

[3]  Behnam Mohammadi-Ivatloo,et al.  Optimal battery technology selection and incentive-based demand response program utilization for reliability improvement of an insular microgrid , 2019, Energy.

[4]  Swapan Kumar Goswami,et al.  Effect of network reconfiguration on power quality of distribution system , 2016 .

[5]  Indrajit N. Trivedi,et al.  Optimal power flow with enhancement of voltage stability and reduction of power loss using ant-lion optimizer , 2016 .

[6]  Almoataz Y. Abdelaziz,et al.  Optimal Placement and Sizing of Distributed Generators in Unbalanced Distribution Systems Using Supervised Big Bang-Big Crunch Method , 2015, IEEE Transactions on Power Systems.

[7]  Kazem Zare,et al.  Optimal performance of microgrid in the presence of demand response exchange: A stochastic multi-objective model , 2019, Comput. Electr. Eng..

[8]  Anh Viet Truong,et al.  Distribution network reconfiguration for power loss minimization and voltage profile improvement using cuckoo search algorithm , 2015 .

[9]  Xiao-Yue Wu,et al.  Reconfiguration of distribution network for loss reduction and reliability improvement based on an enhanced genetic algorithm , 2015 .

[10]  Men-Shen Tsai,et al.  Application of Enhanced Integer Coded Particle Swarm Optimization for Distribution System Feeder Reconfiguration , 2011, IEEE Transactions on Power Systems.

[11]  Taher Niknam,et al.  An efficient multi-objective HBMO algorithm for distribution feeder reconfiguration , 2011, Expert Syst. Appl..

[12]  Ji-Pyng Chiou,et al.  Distribution network reconfiguration for loss reduction by ant colony search algorithm , 2005 .

[13]  E. S. Ali,et al.  Ant Lion Optimization Algorithm for Renewable Distributed Generations , 2016 .

[14]  A. Y. Abdelaziz,et al.  Reconfiguration of distribution systems for loss reduction using the hyper-cube ant colony optimisation algorithm , 2012 .

[15]  M. T. Hagh,et al.  Optimal reliable and resilient construction of dynamic self‐adequate multi‐microgrids under large‐scale events , 2019, IET Renewable Power Generation.

[16]  A. V. Truong,et al.  A novel method based on adaptive cuckoo search for optimal network reconfiguration and distributed generation allocation in distribution network , 2016 .

[17]  Naoto Yorino,et al.  Optimal Distributed Generation Allocation in Distribution Systems for Loss Minimization , 2016, IEEE Transactions on Power Systems.

[18]  Lalit Chandra Saikia,et al.  Automatic generation control of a multi-area system using ant lion optimizer algorithm based PID plus second order derivative controller , 2016 .

[19]  Seyed Abbas Taher,et al.  A novel method for optimal capacitor placement and sizing in distribution systems with nonlinear loads and DG using GA , 2011 .

[20]  Zhong-qiang Wu,et al.  Parameter identification of photovoltaic cell model based on improved ant lion optimizer , 2017 .

[21]  Khaleequr Rehman Niazi,et al.  Adapted ant colony optimization for efficient reconfiguration of balanced and unbalanced distribution systems for loss minimization , 2011, Swarm Evol. Comput..

[22]  Nadarajah Mithulananthan,et al.  Multiple Distributed Generator Placement in Primary Distribution Networks for Loss Reduction , 2013, IEEE Transactions on Industrial Electronics.

[23]  M. Geethanjali,et al.  Application of Modified Bacterial Foraging Optimization algorithm for optimal placement and sizing of Distributed Generation , 2014, Expert Syst. Appl..

[24]  M.A.L. Badr,et al.  Distribution system reconfiguration using a modified Tabu Search algorithm , 2010 .

[25]  Amir Ameli,et al.  A Multiobjective Particle Swarm Optimization for Sizing and Placement of DGs from DG Owner's and Distribution Company's Viewpoints , 2014, IEEE Transactions on Power Delivery.

[26]  Ahmed R. AbulWafa.  A new heuristic approach for optimal reconfiguration in distribution systems , 2011 .

[27]  Mingbo Liu,et al.  Distribution Network Reconfiguration for Loss Reduction and Voltage Stability With Random Fuzzy Uncertainties of Renewable Energy Generation and Load , 2020, IEEE Transactions on Industrial Informatics.

[28]  Santosh Biswas,et al.  Optimal distributed generation placement in shunt capacitor compensated distribution systems considering voltage sag and harmonics distortions , 2014 .

[29]  Davood Azizian,et al.  A multi-objective optimal sizing and siting of distributed generation using ant lion optimization technique , 2017, Ain Shams Engineering Journal.

[30]  Amitava Chatterjee,et al.  Optimum distributed generation placement with voltage sag effect minimization , 2012 .

[31]  T. Jayabarathi,et al.  Power system reconfiguration and loss minimization for an distribution systems using bacterial foraging optimization algorithm , 2012 .

[32]  M.H. Moradi,et al.  A combination of Genetic Algorithm and Particle Swarm Optimization for optimal DG location and sizing in distribution systems , 2010, 2010 Conference Proceedings IPEC.

[33]  Adel M. Sharaf,et al.  Optimized Use of PV Distributed Generation in Voltage Regulation: A Probabilistic Formulation , 2019, IEEE Transactions on Industrial Informatics.