Abstract

The optimal allocation of Distributed Generation (DG) in distribution system is one of the important parts of DG research studies so as to maximize its benefits. For this purpose, a probabilistic approach is proposed in this study to consider time varying load demands as uncertain parameters of distribution system. It is assumed that each load point consists of three categories of voltage dependent loads: residential, industrial and commercial. The proposed algorithm is based on a probabilistic load flow solved by Point Estimate Method (PEM). The objective function is considered as a combination of active power loss, reactive power loss and voltage profiles indices. To solve the optimization problem, an Invasive Weed Optimization (IWO) technique is adopted and the optimal location and size of different types of DG are obtained. Examining on a test distribution system, the performance of the proposed approach is assessed and illustrated.

Keywords:

DG allocation and sizing, Invasive Weed Optimization (IWO), Point Estimate Method (PEM), voltage dependent load,

References

1. Abookazemi, K., M.Y. Hassanand and M.S. Majid, 2010. A review on optimal placement methods of distribution generation sources. Proceeding of IEEE International Conference on Power and Energy. Malaysia, pp: 712-716.
   CrossRef    
2. Borges, C.L. and D.M. Falcão, 2006. Optimal distributed generation allocation for reliability, losses and voltage improvement. Int. J. Elec. Power, 28(6): 413-420.
   CrossRef    
3. Caramia, P., G. Carpinelli and P. Varilone, 2010. Point estimate schemes for probabilistic three-phase load flow. Electr. Pow. Syst. Res., 80(2): 168-175.
   CrossRef    
4. El-Zonkoly, A.M., 2011. Optimal placement of multi-distributed generation units including different load models using particle swarm optimisation. IET Gener. Transm. Dis. J., 5(7): 760-771.
   CrossRef    
5. Eminoglu, U. and M.H. Hocaoglu, 2005. A new power flow method for radial distribution systems including voltage dependent load models. Electr. Pow. Syst. Res., 76(1-3): 106-114.
   CrossRef    
6. Gözel, T. and M.H. Hocaoglu, 2009. An analytical method for the sizing and siting of distributed generators in radial systems. Electr. Pow. Syst. Res., 79(6): 912-918.
   CrossRef    
7. Haghifam, M.R. and O.P. Malik, 2007. Genetic algorithm-based approach for fixed and switchable capacitors placement in distribution systems with uncertainty and time varying loads. IET Gener. Transm. Dis., 1: 244-252.
   CrossRef    
8. Kalantari, M. and A. Kazemi, 2011. Placement of distributed generation unit and capacitor allocation in distribution systems using genetic algorithm. Proceeding of 10th IEEE International Conference on Environment and Electrical Engineering (EEEIC). Rome, pp: 1-5.
   CrossRef    
9. Maciel, R.S., M. Rosa, V. Miranda and A. Padilha-Feltrin, 2012. Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation. Electr. Pow. Syst. Res., 89: 100-108.
   CrossRef    
10. Mehrabian, A.R. and C. Lucas, 2006. A novel numerical optimization algorithm inspired from weed colonization. J. Ecol. Inform., 1: 355-366.
    CrossRef    
11. Moeini-Aghtaie, M., P. Dehghanian and S.H. Hosseini, 2011. Optimal distributed generation placement in a restructured environment via a multi-objective optimization approach. Proceeding of 16th Conference on Electrical Power Distribution Networks (EPDC), Iran.
    
12. Morales, J.M. and J. Pérez-Ruiz, 2007. Point estimate schemes to solve the probabilistic power flow. IEEE Trans. Power Syst., 22(4): 1594-1601.
    CrossRef    
13. Qian, K., C. Zhou, M. Allan and Y. Yuan 2011. Effect of load models on assessment of energy losses in distributed generation planning. Int. J. Elec. Power, 33(6): 1243-1250.
    CrossRef    
14. Shao-Qiang, H. and L. Sen-Mao, 2010. Unbalanced load flow for weakly meshed distribution systems with distributed generation. Proceeding of IEEE International Conference on Electrical and Control Engineering. China, pp: 4513-4517.
    
15. Teng, J.H., 2003. A direct approach for distribution system load flow solutions. IEEE T. Power Syst., 18(3): 882-887.
    CrossRef    
16. Teng, J.H., 2008. Modelling distributed generations in three-phase distribution load flow. IET Gener. Transm. Dis., 2(3): 330-340.
    CrossRef    
17. Venkatesh, B., R. Ranjan and H.B. Gooi, 2004. Optimal recon?guration of radial distribution systems to maximize loadability. IEEE T. Power Syst., 19(1): 260-266.
    CrossRef    
18. Viral, R. and D. Khatod, 2012. Optimal planning of distributed generation systems in distribution system: A review. Renew. Sust. Energ. Rev., 16(7): 5146-5165.
    CrossRef    
19. Walling, R. and G.B. Shattuk, 2007. Distribution transformer thermal behavior and aging in local delivery distribution system. Proceeding of Cired 19th International Conference on Electricity Distribution, Vienna.
    
20. Wang, L. and C. Singh, 2008. Reliability-constrained optimum placement of reclosers and distributed generators in distribution networks using an ant colony system algorithm. IEEE T. Syst. Man Cy. C, 38(6): 757-764.
    CrossRef    
21. Zhang, P. and S.T. Lee, 2004. Probabilistic load fow computation using the method of combined cumulants and gram-charlier expansion. IEEE T. Power Syst., 19(1): 676-682.
    CrossRef    

Competing interests

The authors have no competing interests.

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