Distribution Network Development Planning in the Presence of Distributed Generation Resources by Lightning Search Algorithm
Subject Areas : Renewable Energies PlanningPayam Rokni 1 , Salman Amirkhan 2 , shahab khormali 3 , Mohammad Salehimaleh 4 , javad safaei kuchaksaraei 5 , Siamak Naderi 6
1 - دانشگاه آزاد اسلامی واحد شهمیزاد
2 - Department of Electrical Engineering, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran
3 - Leibniz Supercomputing Centre of the Bavarian Academy of Sciences and Humanities
4 - Faculty of Engineering, Department of Electrical Engineering, University of Mohaghegh Ardabili, Ardabil, Iran.
5 - Department of Power Engineering, Shahmirzad Branch, Islamic Azad University Shahmirzad, Iran
6 - Department of Power Engineering, ShahmirzadBranch, Islamic Azad University, shahmirzad, Iran.
Keywords: Renewable energy sources, Distribution networks, Reduce economic costs, Particle swarm optimization algorithms, Lightning search algorithm,
Abstract :
In recent years, the distribution network has experienced significant growth due to the increasing demand for electric energy. As a result, there is a need to expand the existing distribution network to accommodate more users. In this paper, the focus is on planning the development of electrical energy distribution networks. This involves determining the capacity and optimal location of scattered production sources and choosing the best routes for constructing new lines within the standard 33-bus distribution network. The methods used for this purpose are particle swarm optimization algorithms (PSO) and lightning search. (LSA). Simulation has been done in three scenarios. In the first scenario, the cost reduction of the network development program has been done by locating and determining the capacity of scattered production sources, and in the second scenario, this has been done by constructing new lines in the network. Finally, in the third scenario, locating and determining the optimal capacity of scattered production resources along with the construction of new feeding routes have been done simultaneously by these two algorithms. The results of the simulations indicate that the most effective method for developing electrical energy distribution networks is to simultaneously utilize distributed generation and construct new lines. In this case, network development will have the lowest cost. On the other hand, the proposed lightning search algorithm has been able to perform better than the particle swarm algorithm in all defined scenarios, and with the development program provided by this algorithm, the lowest cost has been obtained.
[1] Bhargava, V., Sinha, S. K., & Dave, M. P. "Voltage Stability Enhancement of Primary Distribution System by Optimal DG Placement". Applications of Artificial Intelligence Techniques in Engineering, vol.1, pp. 65-78, 2019.
[2] Kaveh, M. R., Hooshmand, R. A., & Madani, S. M. "Simultaneous optimization of re-phasing, reconfiguration and DG placement in distribution networks using BF-SD algorithm". Applied Soft Computing, vol. 62, pp. 1044-1055, 2018.
[3] Sultana, U., Khairuddin, A. B., Sultana, B., Rasheed, N., Qazi, S. H., & Malik, N. R. "Placement and sizing of multiple distributed generation and battery swapping stations using grasshopper optimizer algorithm". Energy, vol. 165, pp. 408-421, 2018.
[4] Syahputra, R., Soesanti, I., & Ashari, M. “Performance Enhancement of Distribution Network with DG Integration Using Modified PSO Algorithm”. Journal of Electrical Systems, vol 2, 12(1), 2016.
[5] Kashyap, M., Mittal, A., & Kansal, S. “Optimal Placement of Distributed Generation Using Genetic Algorithm Approach”. In Proceeding of the Second International Conference on Microelectronics, Computing & Communication Systems, vol. 17, pp. 587-597, 2019.
[6] Tooryan, F., & Collins, E. R. “Optimum size and placement of distributed generators in microgrid based on reliability concept”. IEEE Power and Energy Conference at Illinois (PECI), vol.1, pp. 1-6, 2018.
[7] Gkaidatzis, P. A., Bouhouras, A. S., Sgouras, K. I., Doukas, D. I., Christoforidis, G. C., & Labridis, D. P. “Efficient RES Penetration under Optimal Distributed Generation Placement Approach”. Energies, vol.1, 12(7), 1250, 2019.
[8] Pereira S, Ferreira P, Vaz AIF. Generation expansion planning with high share of renewables of variable output. Appl Energy; 190:1275–1288, 2017.
[9] Basso TS, DeBlasio R. IEEE 1547 series of standards: interconnection issues. IEEE Transactions on Power Electronics. 3;19(5):1159-62, 2004.
[10] Canizes B, Soares J, Lezama F, Silva C. Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generation.
[11] Shareef H, Ibrahim AA, Mutlag AH. Lightning search algorithm. Applied Soft Computing; 36:315-33, 2015.
