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The Effect of Distributed Generation Type and Location Constraints on the Solution of the Allocation Algorithm

Rene Prenc(1*), Nikola Bogunović(2), Aleksandar Cuculić(3)

(1) Faculty of Maritime Studies, University of Rijeka, Croatia
(2) Croatian Electric Power Company (HEP), Croatia
(3) Faculty of Maritime Studies, University of Rijeka, Croatia
(*) Corresponding author



Modern planning of power distribution systems faces significant changes over the last few decades due to the massive introduction of distributed generation units. In this paper the authors discuss the inclusion of location constraints for optimal allocation of DG units. The goal function will be the minimization of cumulative average daily active power losses. Four types of DG units will be considered; a solar park, a wind farm, a power station that does not depend on an intermittent primary energy source and a small hydro unit. Each DG unit and network load will be modeled with its own characteristic average daily power production or consumption curve. The network load will consist of residential and industrial consumers. The problem will be solved using genetic algorithm and realized in Matlab programming environment.
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DG Allocation; Location Constraints; Loss Minimization; Genetic Algorithm

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Popović, D. H.; Greatbanks, J. A.; Begović, M.; Pregelj, A. Placement of distributed generators and reclosers for distribution network security and reliability. // International Journal of Electrical Power and Energy Systems, 27, 5-6(2005), pp. 398–408.

Kaluđer, S.; Šljivac, D.; Miletić S. The optimal placement of distributed generation. // Technical Gazette, 19, 3(2012), pp. 535-541.

Mohammadi, M.; Akbari Nasab, M. PSO Based Multiobjective Approach for Optimal Sizing and Placement of Distributed Generation. // Research Journal of Applied Sciences, Engineering and Technology, 2, 8(2011), pp. 832 – 837.

Raj, P.A.; Senthilkumar, S.; Palanivelu, T.G. Swarm intelligence based optimization of distributed generation capacity for power quality improvement. // Acta Elektrotehnica, 49, 3(2008), pp. 334-342.

Harrison, G. P.; Piccolo, A.; Siano, P.; Wallace, A. R. Hybrid GA and OPF evaluation of network capacity for distributed generation connections. // Electric Power Systems Research, 78(2008), pp. 392–398.

Ajay-D-Vimal Raj P.; Senthilkumar, S.; Raja, J.; Ravichandran, S.; Palanivelu, T. G. Optimization of distributed generation capacity for line loss reduction and voltage profile improvement using PSO. // Elektrika, 10, 2(2008), pp. 41-48.

Heydari, M.; Hajizadeh, A.; Banejad, M. Optimal Placement of Distributed Generation Resources. // International Journal of Power System Operation and Energy Management, 1, 2(2011), pp 1–5.

Moravej, Z., Akhlaghi, A., A new approach for DG allocation in distribution network with time variable loads using cuckoo search, (2012) International Review of Electrical Engineering (IREE), 7 (2), pp. 4027-4034.

Hosseini, S.A.; Karami, M.; Karimi Madahi, S. S.; Razavi, F.; Ghandimi, A.A. Finding the Optimal Capacity and Location of Distributed Generation Resources and Analyzing the Impact of Different Coefficient Factors. // Journal of Basic and Applied Scientific Research, 1, 12(2011), pp. 2578 – 2589.

Yammani, C.; Maheswarapu, S.; Matam, S. Optimal Placement of Multi DGs in Distribution System with Considering the DG Bus Available Limits. // Energy and Power, 2, 1(2012), pp. 18 – 23.

Maheswari, S.; Vijayalakshmi, C. Implementation of an Optimization Technique for Improving Power Quality in the Distributed System. // Indian Journal of Computer Science and Engineering, 3, 2(2012), pp. 277 – 281.

Rotaru, F.; Chicco, G.; Grigoras, G; Cartina, G. Two-stage Distributed Generation Optimal Sizing with Clustering-based Node Selection. // International Journal on Electrical Power and Energy Systems (IJEPES), 40, 1(2012), pp. 120–129 .

El-Zonkoly, A. M. Optimal placement of multi DG units including different load models using PSO. // Smart Grid and Renewable Energy, 1(2010), pp. 160-171.

Prenc, R.; Škrlec, D.; Komen, V. A novel load flow algorithm for radial distribution networks with dispersed generation. // Technical Gazette, 20, 6(2013), pp. 969-977.

Barukčić, M.; Hederić, Ž.; Jović, F. Adaption of genetic algorithm for more efficient minimization of active power losses in power network. // Technical Gazette, 15, 3(2008), pp. 11-19.


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