Metaheuristic Optimization Methods for Optimal Power Flow Analysis in DC Distribution Networks
In this paper is addressed the optimal power flow problem in direct current grids, by using solution methods based on metaheuristics techniques and numerical methods. For which was proposed a mixed integer nonlinear programming problem, that describes the optimal power flow problem in direct current grids. As solution methodology was proposed a master–slave strategy, which used in master stage three continuous solution methods for solving the optimal power flow problem: a particle swarm optimization algorithm, a continuous version of the genetic algorithm and the black hole optimization method. In the slave stages was used a methods based on successive approximations for solving the power flow problem, entrusted for calculates the objective function associated to each solution proposed by the master stage. As objective function was used the reduction of power loss on the electrical grid, associated to the energy transport. To validate the solution methodologies proposed were used the test systems of 21 and 69 buses, by implementing three levels of maximum distributed power penetration: 20%, 40% and 60% of the power supplied by the slack bus, without considering distributed generators installed on the electrical grid. The simulations were carried out in the software Matlab, by demonstrating that the methods with the best performance was the BH/SA, due to that show the best trade-off between the reduction of the power loss and processing time, for solving the optimal power flow problem in direct current networks.
Bouchekara, H. (2014). Optimal power flow using black-hole-based optimization approach.Applied Soft Computing,24:879 – 888. doi:https://doi.org/10.1016/j.asoc.2014.08.056.
Bouchekara, H. R. E. H. (2013). Optimal design of electromagnetic devices using a black-hole-based optimizationtechnique.IEEE Trans. Magn., 49(12):5709–5714. doi:10.1109/TMAG.2013.2277694.
Chu, P. and Beasley, J. (1997). A genetic algorithm for the generalised assignment problem.Computers & OperationsResearch, 24(1):17 – 23. doi:https://doi.org/10.1016/S0305-0548(96)00032-9.
Garces, A. (2017). Uniqueness of the power flow solutions in low voltage direct current grids.Electric Power SystemsResearch, 151:149 – 153. doi:https://doi.org/10.1016/j.epsr.2017.05.031.
Garcés, A. (2018). On the convergence of newton’s method in power flow studies for dc microgrids.IEEETransactions on Power Systems, 33(5):5770–5777. doi:10.1109/TPWRS.2018.2820430.
Gil-González, W., Montoya, O. D., Holguín, E., Garces, A., and ña, L. F. G.-N. (2019). Economic dispatch of energystorage systems in dc microgrids employing a semidefinite programming model.Journal of Energy Storage, 21:1 – 8.doi:https://doi.org/10.1016/j.est.2018.10.025.
Grisales-Nore ña, L. F., Gonzalez Montoya, D., and Ramos-Paja, C. A. (2018). Optimal sizing and location ofdistributed generators based on pbil and pso techniques.Energies, 11(4). doi:10.3390/en11041018.
Grisales-Noreña, L. F., Garzon-Rivera, O. D., Danilo Montoya, O., and Ramos-Paja, C. A. (2019). Hybridmetaheuristic optimization methods for optimal location and sizing dgs in dc networks. In Figueroa-García,J. C., Duarte-González, M., Jaramillo-Isaza, S., Orjuela-Cañon, A. D., and Díaz-Gutierrez, Y., editors, AppliedComputer Sciences in Engineering, pages 214–225, Cham. Springer International Publishing.
Grisales-Noreña, L. F., Garzon-Rivera, O. D., Ramírez-Vanegas, C. A., Montoya, O. D., and Ramos-Paja, C. A. (2020). Application of the backward/forward sweep method for solving the power flow problem in DC networks withradial structure.Journal of Physics: Conference Series, 1448:012012. doi:10.1088/1742-6596/1448/1/012012.
Hasan, Z. and El-Hawary, M. E. (2014). Optimal Power Flow by Black Hole Optimization Algorithm. In 2014 IEEE Electrical Power and Energy Conference, pages 134–141. doi:10.1109/EPEC.2014.43.
Kennedy, J. and Eberhart, R. (1995). Particle swarm optimization. InProceedings of ICNN’95 - International Conferenceon Neural Networks, volume 4, pages 1942–1948 vol.4. doi:10.1109/ICNN.1995.488968.
Li, J., Liu, F., Wang, Z., Low, S. H., and Mei, S. (2018). Optimal power flow in stand-alone dc microgrids.IEEETransactions on Power Systems, 33(5):5496–5506. doi:10.1109/TPWRS.2018.2801280.
Mirjalili, S. (2015).The ant lion optimizer.Advances in Engineering Software, 83:80 – 98.doi:https://doi.org/10.1016/j.advengsoft.2015.01.010.
Montoya, O. D., Garrido, V. M., Gil-González, W., and Grisales-Noreña, L. F. (2019). Power flow analysis in dc grids:Two alternative numerical methods. IEEE Transactions on Circuits and Systems II: Express Briefs, 66(11):1865–1869.doi:10.1109/TCSII.2019.2891640.
Montoya, O. D., Gil-González, W., and Garces, A. (2019). Sequential quadratic programming models for solving theOPF problem in DC grids.Electr. Power Syst. Res., 169:18–23. doi:10.1016/j.epsr.2018.12.008.
Montoya, O. D., Gil-González, W., and Grisales-Noreña, L. F. (2018a). Optimal Power Dispatch of DGs in DC PowerGrids: a Hybrid Gauss- Seidel Genetic-Algorithm Methodology for Solving the OPF Problem.WSEAS Transactionson Power Systems, 13:335 – 346.
Montoya, O. D., Grisales-Noreña, L., González-Montoya, D., Ramos-Paja, C., and Garces, A. (2018b). Linearpower flow formulation for low-voltage dc power grids.Electric Power Systems Research, 163:375 – 381.doi:https://doi.org/10.1016/j.epsr.2018.07.003.
Moradi, M. and Abedini, M. (2012). A combination of genetic algorithm and particle swarm optimization foroptimal dg location and sizing in distribution systems.International Journal of Electrical Power and Energy Systems,34(1):66 – 74. doi:https://doi.org/10.1016/j.ijepes.2011.08.023.
Nasir, M., Iqbal, S., and Khan, H. A. (2018). Optimal planning and design of low-voltage low-power solar dcmicrogrids.IEEE Transactions on Power Systems, 33(3):2919–2928. doi:10.1109/TPWRS.2017.2757150.
Piotrowski, A. P., Napiorkowski, J. J., and Rowinski, P. M. (2014). How novel is the novel black hole optimizationapproach?Information Sciences, 267:191 – 200. doi:https://doi.org/10.1016/j.ins.2014.01.026.
Velasquez, O., Giraldo, O. M., Arevalo, V. G., and Grisales-Noreña, L. F. (2019). Optimal power flow in direct-currentpower grids via black hole optimization.Advances in Electrical and Electronic Engineering, 17(1).
Wang, P., Zhang, L., and Xu, D. (2018). Optimal Sizing of Distributed Generations in DC Microgrids with LifespanEstimated Model of Batteries. In2018 21st International Conference on Electrical Machines and Systems (ICEMS), pages2045–2049. doi:10.23919/ICEMS.2018.8549448.