Simultaneous Distribution Network Reconfiguration and Optimal Distributed Generations Integration using a Pareto Evolutionary Algorithm

Imen BEN HAMIDA, Saoussen Brini Salah, Faouzi Msahli, Mouhamed Faouzi Mimouni

Abstract


Several studies of distribution network enhancement focused only on the optimization of either the integration of distributed generations (DG) or network reconfiguration. However, very few researches have been done for distribution network reconfiguration simultaneously with the DG location and sizing. This paper proposes a multi-objective operations management based on network reconfiguration in parallel with DGs allocation and sizing for minimizing active power loss, annual operation costs (installation, maintenance, and active power loss costs) and improving the power system voltage profile. An original Pareto-based evolutionary algorithm is proposed to equally optimize multiple objective functions providing Pareto optimal solutions, where the network manager can select an option. Simulations are successfully carried out on IEEE 33 bus test system for a single and multiple DGs optimal integration. The obtained results show the beneficial effects of applying these multi-objective operations management for multiple DGs integration in the distribution network.


Keywords


Energy saving; Distribution network; Distributed generation; Distribution network reconfiguration; Evolutionary algorithm; Pareto optimality.

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References


A. Merlin and H. Back, “Search for a minimal-loss operating spanning tree configuration in an urban power distribution system,†in Proc. 5th Power System Computation Conf., Cambridge, UK, 1975, pp. 1–18.

T. T. Nguyen and A. V. Truong, “Distribution network reconfiguration for power loss minimization and voltage profile improvement using cuckoo search algorithm,†Int. J. Electr. Power Energy Syst., vol. 68, pp. 233–242, 2015.

M. Abdelaziz, “Distribution network reconfiguration using a genetic algorithm with varying population size,†Electr. Power Syst. Res., vol. 142, pp. 9–11, 2017.

T. Ackermann, G. Andersson, and L. Söder, “Distributed generation: a definition,†Electr. Power Syst. Res., vol. 57, no. 3, pp. 195–204, 2001.

I. Krampitz, “Renewables: making the grid work,†Renew. Energy Focus, vol. 9, no. 6, pp. 20–21, 2008.

W.-S. Tan, M. Y. Hassan, M. S. Majid, and H. A. Rahman, “Optimal distributed renewable generation planning: A review of different approaches,†Renew. Sustain. Energy Rev., vol. 18, pp. 626–645, 2013.

N. Acharya, P. Mahat, and N. Mithulananthan, “An analytical approach for DG allocation in primary distribution network,†Int. J. Electr. Power Energy Syst., vol. 28, no. 10, pp. 669–678, 2006.

A. Hossein Fallahzedh, H. Saeed, and Sohrab Saraneshin, “Distributed Generation Planning & Grid Partitioning for Voltage Control of Smart Distribution System,†International Journal of Renewable Energy Research, 2016.

M. Sara and S. Mahmoud Oukati, “Vector Swarm Optimization Algorithm for Distributed Generation Allocation,†International Journal of Renewable Energy Research, 2013.

T. N. Shukla, S. P. Singh, V. Srinivasarao, and K. B. Naik, “Optimal sizing of distributed generation placed on radial distribution systems,†Electr. Power Compon. Syst., vol. 38, no. 3, pp. 260–274, 2010.

A. El-Fergany, “Optimal allocation of multi-type distributed generators using backtracking search optimization algorithm,†Int. J. Electr. Power Energy Syst., vol. 64, pp. 1197–1205, 2015.

S. R. Gampa and D. Das, “Optimum placement and sizing of DGs considering average hourly variations of load,†Int. J. Electr. Power Energy Syst., vol. 66, pp. 25–40, 2015.

B. Poornazaryan, P. Karimyan, G. B. Gharehpetian, and M. Abedi, “Optimal allocation and sizing of DG units considering voltage stability, losses and load variations,†Int. J. Electr. Power Energy Syst., vol. 79, pp. 42–52, 2016.

A. J. G. Mena and J. A. M. García, “An efficient approach for the siting and sizing problem of distributed generation,†Int. J. Electr. Power Energy Syst., vol. 69, pp. 167–172, 2015.

E. S. Ali, S. A. Elazim, and A. Y. Abdelaziz, “Ant Lion Optimization Algorithm for optimal location and sizing of renewable distributed generations,†Renew. Energy, vol. 101, pp. 1311–1324, 2017.

K. Vinothkumar and M. P. Selvan, “Fuzzy embedded genetic algorithm method for distributed generation planning,†Electr. Power Compon. Syst., vol. 39, no. 4, pp. 346–366, 2011.

M. M. Aman, G. B. Jasmon, A. H. A. Bakar, and H. Mokhlis, “A new approach for optimum simultaneous multi-DG distributed generation Units placement and sizing based on maximization of system loadability using HPSO (hybrid particle swarm optimization) algorithm,†Energy, vol. 66, pp. 202–215, 2014.

W. Sheng, K.-Y. Liu, Y. Liu, X. Meng, and Y. Li, “Optimal placement and sizing of distributed generation via an improved nondominated sorting genetic algorithm II,†IEEE Trans. Power Deliv., vol. 30, no. 2, pp. 569–578, 2015.

K. Nekooei, M. M. Farsangi, H. Nezamabadi-Pour, and K. Y. Lee, “An improved multi-objective harmony search for optimal placement of DGs in distribution systems,†IEEE Trans. Smart Grid, vol. 4, no. 1, pp. 557–567, 2013.

C. Yammani, S. Maheswarapu, and S. K. Matam, “A Multi-objective Shuffled Bat algorithm for optimal placement and sizing of multi distributed generations with different load models,†Int. J. Electr. Power Energy Syst., vol. 79, pp. 120–131, 2016.

A. M. Imran, M. Kowsalya, and D. P. Kothari, “A novel integration technique for optimal network reconfiguration and distributed generation placement in power distribution networks,†Int. J. Electr. Power Energy Syst., vol. 63, pp. 461–472, 2014.

R. S. Rao, K. Ravindra, K. Satish, and S. V. L. Narasimham, “Power loss minimization in distribution system using network reconfiguration in the presence of distributed generation,†IEEE Trans. Power Syst., vol. 28, no. 1, pp. 317–325, 2013.

F. B. Enacheanu, “Outils d’aide à la conduite pour les opérateurs des réseaux de distribution,†Institut National Polytechnique de Grenoble-INPG, 2007.

E. Zitzler, M. Laumanns, L. Thiele, and others, “SPEA2: Improving the strength Pareto evolutionary algorithm,†in Eurogen, 2001, vol. 3242, pp. 95–100.

I. B. Hamida, S. B. Salah, F. Msahli, and M. F. Mimouni, “Strength pareto evolutionary algorithm 2 for Environmental/Economic Power Dispatch,â€Proc. in Modelling, Identification and Control (ICMIC), 2015 7th International Conference on, 2015, pp. 1–6.

A. D. Rana, J. B. Darji, and M. Pandya, “Backward/Forward Sweep Load Flow Algorithm for Radial Distribution System,†Int. J. Sci. Res. Dev., vol. 2, no. 1, pp. 398–400, 2014.

J. B. Kruskal, “On the shortest spanning subtree of a graph and the traveling salesman problem,†Proc. Am. Math. Soc., vol. 7, no. 1, pp. 48–50, 1956.




DOI (PDF): https://doi.org/10.20508/ijrer.v8i1.6789.g7309

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