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Simultaneous Distribution Network Reconfiguration and Optimal Placement of Distributed Generation
Corresponding Author(s) : Abdullahi Bala Kunya
Journal of Applied Materials and Technology, Vol. 1 No. 1 (2019): September 2019
Abstract
A reliable, eco- and nature-friendly operation has been the major concern of modern power system (PS). To improve the PS reliability and reduce the adverse environmental effect of conventional thermal generation facilities, renewable energy based distributed generation (RDG) are being enormously integrated to low and medium voltage distribution networks (DN). However, if these systems are not properly deployed, the reliability and stability of the PS will be endangered and its quality can be dreadfully jeopardized. Among the measures taken to avoid such is optimizing the location and size of each RDG unit in the DNs. These networks are generally operated in a radial configuration, though they can be reconfigured to other topologies to achieve certain objectives. Both RDG placement/sizing and DN reconfiguration are highly non-linear, multi-objective, constrained and combinatorial optimization problems. In this study, a hybrid of Particle Swarm Optimization (PSO) and real-coded Genetic Algorithm (GA) techniques is employed for DN reconfiguration and optimal allocation (size and location) of multiple RDG units in primary DNs simultaneously. The objectives of the proposed technique are active power loss reduction, voltage profile (VP) and feeder load balancing (LB) improvement. It is carried out subject to some technical constraints, with the search space being the set of DN branches, DG sizes and potential locations. To ascertain the effectiveness of the technique, it is implemented on standard IEEE 16-bus, 33-bus and 69-bus test DNs. The proposed algorithm is implemented in MATLAB and MATPOWER environments. It is observed the power loss, voltage deviation and LB are found to be reduced by 32.84%, 12.33% and 24.03% of their respective inherent values in the biggest system when the system is reconfigured only. With the optimized RDGs placed in the reconfigured systems, a further reductions of 46.27%, 25.92% and 36.65% are observed respectively.
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References
L Gomez, F. J. Gonzaleza, "Optimization of distributed generation systems using a new discrete PSO and OPF," Electric Power Systems Research, vol. 84, no. 1, p. 174–180, March 2012.
P. S. Georgilakis and N. D. Hatziargyriou, "Optimal Distributed Generation Placement in Power Distribution Networks: Models, Methods, and Future Research," IEEE Transaction on Power System, vol. 28, no. 3, pp. 3420-3428, 2013.
F. O. Leonardo W. Oliveira, "Optimal reconfiguration of distribution systems with representation of uncertainties through interval analysis," Electrical Power and Energy Systems, vol. 83, p. 382–391, 2016.
H. Fathabadi, "Power distribution network reconfiguration for power loss minimization using novel dynamic fuzzy c-means (dFCM) clustering based ANN approach," Electrical Power and Energy Systems, vol. 78, p. 96–107, 2016.
D. R. s. A. Vesna Borozan, "MINIMUM LOSS RECONFIGURATION OF UNBALANCED DISTRIBUTION NETWORKS," IEEE Transactions on Power Delivery, vol. 12, no. 1, pp. 435-442, January 1997.
M. E. B. a. F. F. Wu, "NETWORK RECONFIGURATION IN DISTRIBUTION SYSTEMS FOR LOSS REDUCTION AND LOAD BALANCING," IEEE Transactions on Power Delivery,, vol. Vol. 4, no. No. 2, pp. 1401-1407, April 1989.
S. Ghasemi, "Balanced and unbalanced distribution networks reconfiguration considering reliability indices," Ain Shams Engineering Journal xxx (2016), vol. xx, p. xxx–xxx, 2016.
V. R. GK and B. PR., "Efficient reconfiguration of balanced and unbalanced distribution systems for loss minimization." IET Generation, Transmission and Distribution. vol. 2, no. 1, p. 7–12, 2008.
N. T. Thanh and T. A. Viet, "Distribution network reconfiguration for power loss minimization and voltage profile improvement using cuckoo search algorithm," Electr Power Energy Syst, vol. 68, p. 233–42., 2015.
A. B. Kunya, G. S. Shehu, A. Y. Ilyasu and S. G. Muhammed, "Distribution Network Reconfiguration for Loss Reduction and Voltage Profile Improvement using B-PSO," in 3rd International Conference on Advanced Technology and Sciences (ICAT’16), Konya, Turkey, 2016.
Y. Ch, S. Goswami and D. Chatterjee, "Effect of network reconfiguration on power quality of distribution System," Electrical Power and Energy Systems, vol. 83, pp. 87-95, 2016.
H. Zhai, M. Yanga, B. Chenb and N. Kang, "Dynamic reconfiguration of three-phase unbalanced distribution networks," Electrical Power and Energy Systems, vol. 99, pp. 1-10, 2018.
E. kianmehr, S. Nikkhah and A. Rabiee, "Multi-Objective Stochastic Model for Joint Optimal Allocation of DG Units and Network Reconfiguration from DG Owner’s and DisCo’s Perspectives," Renewable Energy, pp. 1-13, 2018.
F, O. L. F, M. H and H. N. D, "Assessing the potential of network reconfiguration to improve distributed generation hosting capacity in active distribution systems," IEEE Transaction Power System, vol. 30, no. 1, p. 346–56, 2015.
S. S. P, R. G. S, R. G. K and A. M, "A heuristic method for feeder reconfiguration and service restoration in distribution networks.," International Journal of Electrical Power Energy System, vol. 31, no. 7–8, p. 309–14, 2009.
Q. D and S. LIiuwhe, "Distribution feeder reconfiguration for service restoration and load balancing.," IEEE Transaction Power System, vol. 12, no. 2, p. 724–9, 1997.
G. Zu, J. Xiao and K. Sun, "Distribution network reconfiguration comprehensively considering N−1 security and network loss," IET Generation, Transmission & Distribution, vol. 12, no. 8, pp. 1721-1728, 2018.
T. T. Nguyen, A. V. Truong, Q. T. Nguyen and T. A. Phung, "Multi-objective electric distribution network reconfiguration solution using runner-root algorithm," Applied Soft Computing, vol. 52, pp. 93-108, 2017.
S. R. S. B. C. P. Rabih A. Jabr, "Minimum Loss Network Reconfiguration Using Mixed-Integer Convex Programming," IEEE Transactions on Power Systems, vol. Vol. 27, no. No. 2, pp. 1106-1115, May 2012.
M. R. N. M. H. K. A. A. a. M. J. s. Esmaeil Mahboubi-Moghaddam, "Multi-objective distribution feeder reconfiguration to improve transient stability, and minimize power loss and operation cost using an enhanced evolutionary algorithm at the presence of distributed generations," Electrical Power and Energy Systems, vol. 76, pp. 35-43, 2016.
H. Merlin A, "Search for a minimal loss operating spanning tree configuration in an urban power distribution system," in Proceeding 5th power syst comput conf (PSCC) , Cambridge, UK, vol. 1–18; , 1975.
L. S. M. a. Z. B. Changhyeok Lee, "Robust Distribution Network Reconfiguration," IEEE TRANSACTIONS ON SMART GRID, , vol. Vol. 6, no. No. 2, pp. 836-842, MARCH 2015.
A. M.-A. R. A. K. Abdollah Kavousi-Fard*, "Optimal distribution feeder reconfiguration for increasing the penetration of plug-in electric vehicles and minimizing network costs," Energy, vol. 93, pp. 1693-1703, 2015.
N. T, "An efficient hybrid evolutionary algorithm based on PSO and HBMO algorithms for multi-objective distribution feeder reconfiguration," Energy Conversion Management 2009, vol. 50, p. 2074–82, 2009.
M. J and G. S., "Optimal distribution system reconfiguration using non dominated sorting genetic algorithm (NSGA-II).," Journal of Operation and Automation Power Eng, vol. 1, pp. 12-21, 2013.
R. PV, V. Rama and S. S., "Radial distribution network reconfiguration for loss reduction and load balancing using plant growth simulation algorithm," International Journal of Electrical Engineering, vol. 2, p. 266–77, 2010.
S. A, H. R and K. A, "A new fuzzy optimal reconfiguration of distribution systems for loss reduction and load balancing using ant colony search-based algorithm," Applied Soft Computing, vol. 11, p. 4021–8, 2011.
N. T., "An efficient multi-objective HBMO algorithm for distribution feeder reconfiguration," Expert System Application, vol. 38, p. 2878–87, 2011.
S. D. A. Ahuja and A. Pahwa, "An AIS-ACO hybrid approach for multi-objective distribution system reconfiguration," IEEE transactions on power systems, vol. 22, no. 3, pp. 1101-1111, 2017.
Alonso, D. Oliveira and A. Z. d. Souza, "Artificial immune systems optimization approach for multiobjective distribution system reconfiguration," IEEE Transactions on Power Systems, vol. 30, no. 2, pp. 840-847, 2015.
M.-R. Andervazh, J. Olamaei and M.-R. Haghifam, "Adaptive multi-objective distribution network reconfiguration using multi-objective discrete particles swarm optimisation algorithm and graph theory," IET Generation, Transmission & Distribution, vol. 7, no. 12, pp. 1367-1382, 2013.
U. Din, "Efficient sizing and placement of distributed generators in cyber-physical power system," Journal of System Architecture, vol. 23, no. 1, pp. 1-12, 2019.
M. J. Hadidian-Moghaddam, S. Arabi-Nowdeh, M. Bigdeli and D. Azizian, "A multi-objective optimal sizing and siting of distributed generation using ant lion optimization technique," Ain Shams Engineering Journal, vol. 9, p. 2101–2109, 2018.
R. Prabha and J. T, "Optimal placement and sizing of multiple distributed generating units in distribution networks by invasive weed optimization algorithm," Ain Shams Engineering Journal, vol. 7, no. 2, p. 683–94, 2016.
T. A. P. c. Thuan Thanh Nguyen Anh Viet Truong a, "A novel method based on adaptive cuckoo search for optimal network reconfiguration and distributed generation allocation in distribution network," Electrical Power and Energy Systems, vol. 78, p. 801–815, 2016.
B. Tolabi, M. H. Ali and M. Rizwan, "Simultaneous Reconfiguration, Optimal Placement of DSTATCOM, and Photovoltaic Array in a Distribution System Based on Fuzzy-ACO Approach," IEEE Transaction on Sustainable Energy , vol. 6, no. 1, pp. 210-218, 2015.
A.F. Ali and M. A.Tawhid, "A hybrid particle swarm optimization and genetic algorithm with population partitioning for large scale optimization problems," Ain Shams Engineering Journal, vol. 8, no. 2, pp. 191-206, 2017.
D. T. L. M. A. Kashem, M. Negnevitsky and G. Ledwich, "Maximising Voltage Support in Distribution Systems by Distributed Generation," in TENCON 2005 - 2005 IEEE Region 10 Conference, Melbourne, Qld., Nov. 2005.
