Two States for Optimal Position and Capacity of Distributed Generators Considering Network Reconfiguration for Power Loss Minimization Based on Runner Root Algorithm

Although the distributed generator (DG) placement and distribution network (DN) reconfiguration techniques contribute to reduce power loss, obviously the former is a design problem which is used for a long-term purpose while the latter is an operational problem which is used for a short-term purpose. In this situation, the optimal value of the position and capacity of DGs is a value which must be not affected by changing the operational configuration due to easy changes in the status of switches compared with changes in the installed location of DG. This paper demonstrates a methodology for choosing the position and size of DGs on the DN that takes into account re-switching the status of switches on distribution of the DN to reduce power losses. The proposed method is based on the runner root algorithm (RRA) which separates the problem into two states. In State-I, RRA is used to optimize the position and size of DGs on closed-loop distribution networks which is a mesh shape topology and power is delivered through more than one line. In State-II, RRA is used to reconfigure the DN after placing the DGs to find the open-loop distribution network which is a tree shape topology and power is only delivered through one line. The calculation results in DN systems with 33 nodes and 69 nodes, showing that the proposed method is capable of solving the problem of the optimal position and size of DGs considering distribution network reconfiguration.

[1]  Javad Olamaei,et al.  Optimal placement and sizing of DG (distributed generation) units in distribution networks by novel hybrid evolutionary algorithm , 2013 .

[2]  Eskandar Gholipour,et al.  Decreasing activity cost of a distribution system company by reconfiguration and power generation control of DGs based on shuffled frog leaping algorithm , 2014 .

[3]  F. Merrikh Bayat,et al.  The runner-root algorithm: A metaheuristic for solving unimodal and multimodal optimization problems inspired by runners and roots of plants in nature , 2015, Appl. Soft Comput..

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

[5]  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..

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

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

[8]  Tuba Gozel,et al.  An analytical method for the sizing and siting of distributed generators in radial systems , 2009 .

[9]  T. Jayabarathi,et al.  Optimal placement and sizing of multiple distributed generating units in distribution networks by invasive weed optimization algorithm , 2016 .

[10]  Roohollah Fadaeinedjad,et al.  Distribution system efficiency improvement using network reconfiguration and capacitor allocation , 2015 .

[11]  Felix F. Wu,et al.  Network Reconfiguration in Distribution Systems for Loss Reduction and Load Balancing , 1989, IEEE Power Engineering Review.

[12]  Ramesh C. Bansal,et al.  An optimal investment planning framework for multiple distributed generation units in industrial distribution systems , 2014 .

[13]  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 .

[14]  Chandan Kumar Chanda,et al.  Placement of wind and solar based DGs in distribution system for power loss minimization and voltage stability improvement , 2013 .

[15]  A. Berizzi,et al.  Distributed generation planning using genetic algorithms , 1999, PowerTech Budapest 99. Abstract Records. (Cat. No.99EX376).

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

[17]  Mostafa Sedighizadeh,et al.  Application of the hybrid Big Bang-Big Crunch algorithm to optimal reconfiguration and distributed generation power allocation in distribution systems , 2014 .

[18]  Thang Trung Nguyen,et al.  Multi-objective electric distribution network reconfiguration solution using runner-root algorithm , 2017, Appl. Soft Comput..

[19]  M. Subramaniyan,et al.  Optimal reconfiguration/distributed generation integration in distribution system using adaptive weighted improved discrete particle swarm optimization , 2019, COMPEL - The international journal for computation and mathematics in electrical and electronic engineering.

[20]  Hsiao-Dong Chiang,et al.  Optimal network reconfigurations in distribution systems. II. Solution algorithms and numerical results , 1990 .

[21]  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.

[22]  M. Haghifam,et al.  Adaptive multi-objective distribution network reconfiguration using multi-objective discrete particles swarm optimisation algorithm and graph theory , 2013 .

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

[24]  Dheeraj Joshi,et al.  A hybrid teaching–learning-based optimization technique for optimal DG sizing and placement in radial distribution systems , 2018, Soft Comput..

[25]  Vishal Kumar,et al.  Optimal placement of different type of DG sources in distribution networks , 2013 .

[26]  K. Zare,et al.  Application of binary group search optimization to distribution network reconfiguration , 2014 .

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

[28]  Farshad Merrikh-Bayat,et al.  The runner-root algorithm , 2015 .

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

[30]  J. J. Grainger,et al.  Distribution feeder reconfiguration for loss reduction , 1988 .