|تعداد مشاهده مقاله||3,524,073|
|تعداد دریافت فایل اصل مقاله||2,332,489|
Co-Evolutionary Multi-Swarm PSO Based Optimal Placement of Miscellaneous DGs in a Real Electricity Grids Regarding Uncertainties
|Journal of Operation and Automation in Power Engineering|
|دوره 10، شماره 1، تیر 2022، صفحه 71-79 اصل مقاله (669.99 K)|
|نوع مقاله: Research paper|
|شناسه دیجیتال (DOI): 10.22098/joape.2022.8128.1562|
|G. Derakhshan* 1؛ H. Shahsavari2؛ A. Safari3|
|1Department of Electrical Engineering, Damavand Branch, Islamic Azad University, Tehran, Iran|
|2Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran|
|3Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran|
|Distributed generators (DGs) facilitate minimizing a monetary objective for controlling overload or low-voltage obstacles. In conjunction with controlling such complications, a DG unit can be allocated for maximum reliability or efficiency. This study presents a new method based on a new index for locating and sizing DGs in electricity distribution systems. Stable node voltages which are known as power stability index (PSI) are considered in developing the index. An analytical method is applied in visualizing the effect of DG on losses, voltage profile, and voltage stability of the system. In this study, a new approach using co-evolutionary multi-swarm particle swarm optimization (CMPSO) algorithm is purposed for locating DGs in radial electrical distribution systems considering the uncertainty of solar power as well as load and wind power. In this paper, the optimal locations and sizes of DG units are calculated by considering the active power loss, reliability index, and PSI as objective functions. The presented algorithm is tested on 33-bus and 274-bus real distribution networks. The results of the simulation show the effectiveness of the proposed method.|
|Distributed generators (DGs)؛ Co-evolutionary multi-swarm particle swarm optimization (CMPSO)؛ Uncertainty؛ Power stability index؛ Real distribution network|
 G. Pepermans et al., “Distributed generation: definition, benefits and issues”, Energy policy, vol. 33, pp. 787-98, 2005.
 J. Lopes et al., “Integrating distributed generation into electric power systems: A review of drivers, challenges and opportunities”, Electr. Power Syst. Res., vol. 77, pp. 1189-203, 2007.
 F. Jabari, S. Asadi, S. Seyed-barhagh, “A Novel forward-backward sweep based optimal DG placement approach in radial distribution systems”, Optimiz. Power Syst. Prob., pp. 49-51, 2020.
 S. Oudjana et al., “Optimal placement of distributed generation based PV source in electrical power system for LVSI improvement using GA algorithm”, Inter. Conf. Artificial Intell. Renew. Energetic Syst., 2020.
 E. Almabsout et al., “A hybrid local Search-Genetic algorithm for simultaneous placement of DG units and shunt capacitors in radial distribution systems”, IEEE Access, vol. 8, pp. 54465-81, 2020.
 T. Griffin et al., “Placement of dispersed generations systems for reduced losses”, 33rd Inter. Conf. Sci., 2000.
 W. Tan et al., “Optimal distributed renewable generation planning: A review of different approaches”, Renew. Sustain. Energy Rev., vol. 18, pp. 626-45, 2013.
 P. Prakash, D. Khatod, “Optimal sizing and siting techniques for distributed generation in distribution systems: A review”, Renew. Sustain. Energy Rev., vol. 57, pp. 111-30, 2016.
 C. Wang, M. Nehrir, “Analytical approaches for optimal placement of distributed generation sources in power systems”, IEEE Trans. Power Syst., vol. 19, pp. 2068-76, 2004.
 A. Tah, D. Das, “Novel analytical method for the placement and sizing of distributed generation unit on distribution networks with and without considering P and PQV buses”, Int. J. Electr. Power Energy Syst., vol. 1, pp. 401-413, 2016.
 R. Jabr, B. Pal, “Ordinal optimization approach for locating and sizing of distributed generation”, IET Gener., Transm. Distrib., vol. 3, pp. 713-23, 2009.
 Z. Moravej, A. Akhlaghi, “A novel approach based on cuckoo search for DG allocation in distribution network”, Int. J. Electr. Power Energy Syst., vol. 44, pp. 672-9, 2013.
 U. Sultana et al., “Sultana B. Grey wolf optimizer based placement and sizing of multiple distributed generation in the distribution system”, Energy, vol. 111, pp. 525-36, 2016.
 M. Vatani et al., “Multiple distributed generation units allocation in distribution network for loss reduction based on a combination of analytical and genetic algorithm methods”, IET Gener. Transm. Distrib., vol. 10, pp. 66-72, 2016.
 S. Kumar et al., “A novel opposition-based tuned-chaotic differential evolution technique for techno-economic analysis by optimal placement of distributed generation”, Eng. Optimiz., vol. 52, pp. 303-24, 2020.
 P. Huy et al., “Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage”, Energy, vol. 195, pp. 117011, 2020.
 G. Memarzadeh, F. Keynia, “A new index‐based method for optimal DG placement in distribution networks”, Eng. Rep., vol. 2, pp. 12243, 2020.
 I. Quadri, S. Bhowmick, D. Joshi, “A comprehensive technique for optimal allocation of distributed energy resources in radial distribution systems”, Appl. Energy, vol. 211, pp. 1245-60, 2018.
 P. Jahangiri, M. Fotuhi-Firuzabad, “Reliability assessment of distribution system with distributed generation”, Power Energy Conf., 2016.
 K. Kela, L. Arya, “Reliability optimization of radial distribution systems employing differential evolution and bare bones particle swarm optimization”, J. Ins. Eng., vol. 95, pp. 231-9, 2014.
 A. Hassan, Y. Sun, Z. Wang, “Optimization techniques applied for optimal planning and integration of renewable energy sources based on distributed generation: Recent trends”, Cogent Eng., vol. 7, pp. 1766394, 2020.
 O. Oluwole, “Optimal allocation of distributed generation for power loss reduction and voltage profile improvement”, Uni. Cape Town, 2016.
 P. Mohanty, D. Lal, “Voltage stability index and butterfly optimization algorithm-based DG placement and sizing in electrical power distribution system”, Green Tech. Smart City Soc., 2021.
 J. Pengelly, “Monte carlo methods,” Uni. Otago, 2002.
 E. Ali, S. Elazim, A. Abdelaziz, “Ant lion optimization algorithm for optimal location and sizing of renewable distributed generations”, Renew. Energy. vol. 101, pp. 1311-24, 2017.
 Z. Zhan et al., “Multiple populations for multiple objectives: A coevolutionary technique for solving multiobjective optimization problems”, IEEE Trans. Cybernetics, vol. 43, pp. 445-63, 2013.
 M. Kashem et al., “A novel method for loss minimization in distribution networks”, Proc. Int. Conf. Electric Utility Deregul. Restruct. Power Tech., 2000.
 B. Dougherty, A. Fanney, M. Davis, “Measured performance of building integrated photovoltaic panels”, Int. Solar Energy Conf., 2004.
 M. Kumar, P. Nallagownden, I. Elamvazuthi, “Optimal placement and sizing of renewable distributed generations and capacitor banks into radial distribution systems”, Energies, vol. 10, pp. 811, 2017.
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