Optimal Sizing and Placement of Multiple DGs in Distribution Network to Reduce Total Loss Using Cuckoo Search Optimization

This work proposed a method for the best placement and sizing of the Distributed Generations (DGs) in the distribution systems network with aim to minimize the the total system losses. The total system losses includes the resultant of real power loss and reactive power loss. The main aim of presented work is to minimize the system losses and also to enhance the system's voltage profile. This paper is made from the fact that DGs are more advantageous to achieve the demand of power that are close to the load centers compared to those at the centralized power generation. This work considers 85-bus radial distribution network (RDN) for DG planning based on objective to minimize overall MVA losses of system. The desired objective is carried out with the help of MATPOWER/MATLAB and the comparison of obtained results with DG using cuckoo search algorithm is presented related to the base case results. At last, it can be concluded that cuckoo search is an efficient methodology for optimal size and placement of DGs.

[1]  Jia Liu,et al.  Decentralized stochastic optimization based planning of integrated transmission and distribution networks with distributed generation penetration , 2018, Applied Energy.

[2]  Aashish Kumar Bohre,et al.  Optimal Distribution Network Reconfiguration to Improve the System Performances using PSO with Multiple-Objectives , 2020, 2020 International Conference on Computational Intelligence for Smart Power System and Sustainable Energy (CISPSSE).

[3]  Uma Nangia,et al.  Optimal Sizing of Renewable Energy Resources in a Microgrid for a Distributed Generation System , 2019, 2019 International Symposium on Advanced Electrical and Communication Technologies (ISAECT).

[4]  Dheeraj Kumar Khatod,et al.  Techno-economic and environmental approach for optimal placement and sizing of renewable DGs in distribution system , 2017 .

[5]  Ramesh C. Bansal,et al.  Simultaneous allocation of distributed energy resource using improved particle swarm optimization , 2017 .

[6]  Jose Roberto Sanches Mantovani,et al.  A decomposition approach for integrated planning of primary and secondary distribution networks considering distributed generation , 2019 .

[7]  Manisha Dubey,et al.  Optimal sizing and sitting of DG with load models using soft computing techniques in practical distribution system , 2016 .

[8]  Mostafa Sedighizadeh,et al.  Multi-objective optimal reconfiguration and DG (Distributed Generation) power allocation in distribution networks using Big Bang-Big Crunch algorithm considering load uncertainty , 2016 .

[9]  Ali Ehsan,et al.  Optimal integration and planning of renewable distributed generation in the power distribution networks: A review of analytical techniques , 2018 .

[10]  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..

[11]  Dheeraj Joshi,et al.  A comprehensive technique for optimal allocation of distributed energy resources in radial distribution systems , 2018 .

[12]  Martin Braun,et al.  Hosting capacity of low-voltage grids for distributed generation: Classification by means of machine learning techniques , 2018, Appl. Soft Comput..

[13]  Zuo Sun,et al.  Advances on Distributed Generation Technology , 2012 .

[14]  Jen-Hao Teng,et al.  Modelling distributed generations in three-phase distribution load flow , 2008 .

[15]  Tomasz Sikorski,et al.  Distributed Generation and Its Impact on Power Quality in Low-Voltage Distribution Networks , 2015 .

[16]  Mihail Abrudean,et al.  Effects of Distributed Generation on Electric Power Systems , 2014 .

[17]  S. M. Moghaddas-Tafreshi,et al.  Distributed generation modeling for power flow studies and a three-phase unbalanced power flow solution for radial distribution systems considering distributed generation , 2009 .

[18]  Bo Wang,et al.  Research on solving the optimal sizing and siting of distributed generation , 2017 .

[19]  Seema Singh,et al.  Distributed Generation in Power Systems: An Overview and Key Issues , 2009 .

[20]  Wei Gu,et al.  Optimal siting and sizing of distributed generation in distribution systems with PV solar farm utilized as STATCOM (PV-STATCOM) , 2018 .

[21]  Xin-She Yang,et al.  Cuckoo Search via Lévy flights , 2009, 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC).

[22]  Mehmet Emin Meral,et al.  A flexible control strategy with overcurrent limitation in distributed generation systems , 2019, International Journal of Electrical Power & Energy Systems.

[23]  N.N. Schulz,et al.  Development of Three-Phase Unbalanced Power Flow Using PV and PQ Models for Distributed Generation and Study of the Impact of DG Models , 2007, IEEE Transactions on Power Systems.