An improved sine-cosine algorithm for simultaneous network reconfiguration and DG allocation in power distribution systems

Abstract This paper presents a recently proposed meta-heuristic sine–cosine algorithm combined with levy flights to reconfigure the distribution network with simultaneous allocation (placement and size) of multiple distributed generators (DGs). The algorithm is proposed to be adaptive with an exponentially decreasing conversion parameter and a self-controlled levy mutation in order to explore the solution space more efficiently during the course of iterations. The effectiveness of the algorithm is verified on 10 standard benchmark functions. Later, it is used to address the issues of a real combinatorial optimization, such as network reconfiguration (NR) in the presence of DGs. In order to enhance the effectiveness of the system, a multi-objective function is developed considering total active power loss and overall voltage stability of the network with suitable weights without violating the system limitations. To evaluate the objective function, a depth fast search integrated forward–backward sweep based load flow technique that is capable of managing any topological alterations owing to the NR and DG integration is developed. In order to demonstrate the efficiency of the system, four distinct cases of NR and DG installation are investigated. The proposed algorithm is contrasted with other well-known algorithms that exist in the literature, namely, harmony search algorithm (HSA), fireworks algorithm (FWA), genetic algorithm (GA), refined genetic algorithm (RGA) and firefly (FF) algorithm considering 33 and 69-bus distribution systems at three different load levels and its superiority is established.

[1]  Seyedali Mirjalili,et al.  SCA: A Sine Cosine Algorithm for solving optimization problems , 2016, Knowl. Based Syst..

[2]  Sivkumar Mishra,et al.  A comprehensive review on power distribution network reconfiguration , 2017 .

[3]  Hazlie Mokhlis,et al.  Minimum switching losses for solving distribution NR problem with distributed generation , 2017 .

[4]  Sivkumar Mishra,et al.  A simple algorithm for distribution system load flow with distributed generation , 2014, International Conference on Recent Advances and Innovations in Engineering (ICRAIE-2014).

[5]  Nantiwat Pholdee,et al.  Adaptive Sine Cosine Algorithm Integrated with Differential Evolution for Structural Damage Detection , 2017, ICCSA.

[6]  Provas Kumar Roy,et al.  Krill herd algorithm for optimal location of distributed generator in radial distribution system , 2016, Appl. Soft Comput..

[7]  Roohollah Fadaeinedjad,et al.  Energy Loss Minimization in Distribution Systems Utilizing an Enhanced Reconfiguration Method Integrating Distributed Generation , 2015, IEEE Systems Journal.

[8]  Vo Ngoc Dieu,et al.  Improved stochastic fractal search algorithm with chaos for optimal determination of location, size, and quantity of distributed generators in distribution systems , 2018, Neural Computing and Applications.

[9]  Behrooz Vahidi,et al.  Reconfiguration of Smart Distribution Network in the Presence of Renewable DG’s Using GWO Algorithm , 2017 .

[10]  J. Z. Zhu,et al.  Optimal reconfiguration of electrical distribution network using the refined genetic algorithm , 2002 .

[11]  Aboul Ella Hassanien,et al.  ASCA-PSO: Adaptive sine cosine optimization algorithm integrated with particle swarm for pairwise local sequence alignment , 2018, Expert Syst. Appl..

[12]  Sivkumar Mishra,et al.  A robust load flow algorithm to solve power distribution network reconfiguration problem with a population based meta-heuristic approach , 2017, 2017 6th International Conference on Computer Applications In Electrical Engineering-Recent Advances (CERA).

[13]  M. Hariharan,et al.  Sine–cosine algorithm for feature selection with elitism strategy and new updating mechanism , 2017, Neural Comput. Appl..

[14]  N. Zareen,et al.  Grey wolf optimizer based placement and sizing of multiple distributed generation in the distribution system , 2016 .

[15]  D. Das,et al.  Impact of Network Reconfiguration on Loss Allocation of Radial Distribution Systems , 2007, IEEE Transactions on Power Delivery.

[16]  N. Mithulananthan,et al.  Loss reduction and loadability enhancement with DG: A dual-index analytical approach , 2014 .

[17]  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 .

[18]  Zuhairi Baharudin,et al.  One rank cuckoo search algorithm for optimal placement of multiple distributed generators in distribution networks , 2017, TENCON 2017 - 2017 IEEE Region 10 Conference.

[19]  M. Kowsalya,et al.  A new power system reconfiguration scheme for power loss minimization and voltage profile enhancement using Fireworks Algorithm , 2014 .

[20]  Hany M. Hasanien,et al.  Optimal power flow solution in power systems using a novel Sine-Cosine algorithm , 2018, International Journal of Electrical Power & Energy Systems.

[21]  R. M. Rizk-Allah,et al.  Hybridizing sine cosine algorithm with multi-orthogonal search strategy for engineering design problems , 2018, J. Comput. Des. Eng..

[22]  I. Elamvazuthi,et al.  A Quasi-Oppositional-Chaotic Symbiotic Organisms Search algorithm for optimal allocation of DG in radial distribution networks , 2020, Appl. Soft Comput..

[23]  Usharani Raut,et al.  A Fast Heuristic Network Reconfiguration Algorithm to Minimize Loss and Improve Voltage Profile for a Smart Power Distribution System , 2017, 2017 International Conference on Information Technology (ICIT).

[24]  Dieu Ngoc Vo,et al.  Stochastic fractal search algorithm for reconfiguration of distribution networks with distributed generations , 2020 .

[25]  I. Elamvazuthi,et al.  An improved meta-heuristic method to maximize the penetration of distributed generation in radial distribution networks , 2019, Neural Computing and Applications.

[26]  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..

[27]  Morad Abdelaziz,et al.  Distribution network reconfiguration using a genetic algorithm with varying population size , 2017 .

[28]  D. Das A fuzzy multiobjective approach for network reconfiguration of distribution systems , 2006, IEEE Transactions on Power Delivery.

[29]  Irraivan Elamvazuthi,et al.  Optimal Placement and Sizing of Renewable Distributed Generations and Capacitor Banks into Radial Distribution Systems , 2017 .

[30]  M. M. Aman,et al.  A new approach for optimum simultaneous multi-DG distributed generation Units placement and sizing based on maximization of system loadability using HPSO (hybrid particle swarm optimization) algorithm , 2014 .

[31]  Dieu Ngoc Vo,et al.  A novel stochastic fractal search algorithm for optimal allocation of distributed generators in radial distribution systems , 2018, Appl. Soft Comput..

[32]  Belkacem Mahdad,et al.  A new interactive sine cosine algorithm for loading margin stability improvement under contingency , 2017 .

[33]  Parimal Acharjee,et al.  Application of efficient self-adaptive differential evolutionary algorithm for voltage stability analysis under practical security constraints , 2013, Appl. Math. Comput..

[34]  M. Kowsalya,et al.  A novel integration technique for optimal network reconfiguration and distributed generation placement in power distribution networks , 2014 .

[35]  Aboul Ella Hassanien,et al.  Sine cosine optimization algorithm for feature selection , 2016, 2016 International Symposium on INnovations in Intelligent SysTems and Applications (INISTA).

[36]  H. Mokhlis,et al.  Optimum tie switches allocation and DG placement based on maximisation of system loadability using discrete artificial bee colony algorithm , 2016 .

[37]  I. Drezga,et al.  A heuristic nonlinear constructive method for distribution system reconfiguration , 1999 .

[38]  Pandian Vasant,et al.  Symbiotic Organism Search Algorithm for Optimal Size and Siting of Distributed Generators in Distribution Systems , 2017, Int. J. Energy Optim. Eng..

[39]  S. Carneiro,et al.  A new heuristic reconfiguration algorithm for large distribution systems , 2005, 2006 IEEE Power Engineering Society General Meeting.

[40]  M. Raju,et al.  Optimal Network Reconfiguration of Large-Scale Distribution System Using Harmony Search Algorithm , 2011, IEEE Transactions on Power Systems.

[41]  Bijaya Ketan Panigrahi,et al.  A multi objective approach for placement of multiple DGs in the radial distribution system , 2018, Int. J. Mach. Learn. Cybern..

[42]  Mohamed Faouzi Mimouni,et al.  Optimal network reconfiguration and renewable DG integration considering time sequence variation in load and DGs , 2018 .

[43]  Usharani Raut,et al.  An improved Elitist–Jaya algorithm for simultaneous network reconfiguration and DG allocation in power distribution systems , 2019, Renewable Energy Focus.

[44]  H. Ghasemi,et al.  Voltage Stability-Based DG Placement in Distribution Networks , 2013, IEEE Transactions on Power Delivery.

[45]  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.

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

[47]  Chuanpei Xu,et al.  A Multi-Verse Optimizer with Levy Flights for Numerical Optimization and Its Application in Test Scheduling for Network-on-Chip , 2016, PloS one.

[48]  D. Ernst,et al.  A biased random key genetic algorithm applied to the electric distribution network reconfiguration problem , 2017, Journal of Heuristics.

[49]  G. B. Jasmon,et al.  A new approach of distribution system reconfiguration for loss minimization , 2000 .

[50]  Niladri Chakraborty,et al.  Optimal DG placement by multi-objective opposition based chaotic differential evolution for techno-economic analysis , 2019, Appl. Soft Comput..