Czasopismo | PRZEGLĄD ELEKTROTECHNICZNY | Rocznik 2024 - zeszyt 7

Allocation of Photovoltaic and Wind Turbine Based DG Units Using the Energy Valley Optimizer (EVO) algorithm.

Alokacja jednostek DG wykorzystujących fotowoltaikę i turbiny wiatrowe przy użyciu algorytmu Energy Valley Optimizer (EVO)

10.15199/48.2024.07.45

nr katalogowy: 149546
10.15199/48.2024.07.45

Streszczenie

In this paper, we introduce a novel meta-heuristic technique called the Energy Valley Optimizer (EVO) algorithm designed for the optimization of distributed generation (DG) allocation within distribution networks (DN). The proposed algorithm focuses on the efficient placement of DG units based on photovoltaic (PV) and wind turbine (WT) technologies. Drawing inspiration from advanced physics principles, particularly those related to stability and various modes of particle decay, the EVO algorithm seeks to minimize both total power and energy losses in the DN. To assess its efficacy, the presented technique is applied to problem instances aimed at minimizing power and energy losses, respectively. The evaluation of the proposed approach is conducted using the IEEE 33-bus test system as a case study. The effectiveness of the EVO method is substantiated through a comparative analysis, wherein simulation results are juxtaposed with those obtained from other optimization algorithms recently developed in the literature.

Abstract

W artykule przedstawiamy nowatorską technikę metaheurystyczną zwaną algorytmem Energy Valley Optimizer (EVO) zaprojektowaną w celu optymalizacji alokacji generacji rozproszonej (DG) w sieciach dystrybucyjnych (DN). Zaproponowany algorytm skupia się na efektywnym rozmieszczeniu jednostek DG w oparciu o technologie fotowoltaiczne (PV) i turbiny wiatrowe (WT). Czerpiąc inspirację z zaawansowanych zasad fizyki, szczególnie tych związanych ze stabilnością i różnymi trybami rozpadu cząstek, algorytm EVO stara się minimalizować zarówno całkowite straty mocy, jak i energii w DN. Aby ocenić skuteczność, przedstawioną technikę stosuje się do przypadków problemowych mających na celu minimalizację odpowiednio strat mocy i energii. Ocena proponowanego podejścia została przeprowadzona przy użyciu systemu testowego IEEE 33-bus jako studium przypadku. Skuteczność metody EVO potwierdzono analizą porównawczą, podczas której wyniki symulacji zestawiono z wynikami uzyskanymi z innych algorytmów optymalizacyjnych opracowanych ostatnio w literaturze.

Słowa kluczowe

Keywords

Bibliografia

[1] REFERENCES O. M. Babatunde, J. L. Munda, and Y. Hamam, “A comprehensive state-of-the-art survey on hybrid renewable energy system operations and planning”, IEEE Access, vol. 8, pp. 75313–75346, https://doi.org/10.1109/access.2020.2988397
[2] 2020. O. M. Babatunde, J. L. Munda, and Y. Hamam, “A comprehensive state-of-the-art survey on power generation expansion planning with intermittent renewable energy source and energy storage”, International Journal of Energy Research, vol. 43, no. 12, https://doi.org/10.1002/er.4388 pp. 6078–6107, 2019.
[3] O. M. Babatunde, J. L. Munda, and Y. Hamam, “Selection of a hybrid renewable energy systems for a lowincome household”, Sustainability, vol. 11, no. 16, 4282, 2019.
[16] https://doi.org/10.3390/su11164282
[4] P. Prakash, and D. K. Khatod, “Optimal sizing and siting techniques for distributed generation in distribution systems: A review”, Renewable and Sustainable Energy Reviews, vol. 57, pp. 111–130, 2016. https://doi.org/10.1016/j.rser.2015.12.099
[5] M. D. A. Al-falahi, S. D. G. Jayasinghe, and H. Enshaei, “A review on recent size optimization methodologies for standalone solar and wind hybrid renewable energy system”, Energy Conversion and Management, vol. 143, pp. 252–274, 2017. https://doi.org/10.1016/j.enconman.2017.04.019 Urinboy, Jalilov, and Mansur Hasanov. “Improvement Performance of Radial Distribution System by Optimal Placement of Photovoltaic Array.” International Journal of Engineering and Information Systems (IJEAIS) 5.2 (2021): 157 159.
[17] K amel, Salah, et al. “Radial Distribution System Reconfiguration for Real Power Losses reduction by Using Salp Swarm Optimization Algorithm.” 2019 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia). IEEE, 2019.
[6] T. Adefarati, and B. C. Bansal, “Integration of renewable distributed generators into the distribution system: A review”, IET Renewable Power Generation, vol. 10, no. 7, pp.873 884,2016.https://doi.org/10.1049/iet-rpg.2015.0378
[7] A. A. Saleh, T. Senjyu, S. Alkhalaf, M. A. Alotaibi, and A. M. Hemeida, “Water cycle algorithm for probabilistic planning of renewable energy resource, considering different load models”, Energies, vol. 13, no. https://doi.org/10.3390/en13215800 21, 5800, 2020.
[8] S. A. Memon, and R. N. Patel, “An overview of optimization techniques used for sizing of hybrid renewable energy systems”, Renewable Energy Focus, vol. 39, pp. 1 26,2021.https://doi.org/10.1016/j.ref.2021.07.007
[9] Y. Zhou, C. Wang, J. Wu, J. Wang, M. Cheng, and G. Li, “Optimal scheduling of aggregated thermostatically controlled loads with renewable generation in the intraday electricity market,” Applied energy, vol. 188, pp. 456-465, 2017.
[10] Prakash, D.B., Lakshminarayana, C. (2018). Multiple DG placements in radial distribution system for multi objectives using Whale Optimization Algorithm. Alexandria Engineering Journal, 57(4): https://doi.org/10.1016/j.aej.2017.11.003 2797-2806.
[11] Rama Prabha, D., Jayabarathi, T. (2016). Optimal placement and sizing of multiple distributed generating units in distribution networks by invasive weed optimization algorithm. Ain Shams Engineering Journal, 7(2): https://doi.org/10.1016/j.asej.2015.05.014 683-694.
[12] Mareddy, P.L., Reddy, S., Reddy, V.C.V. (2010). Optimal DG placement for maximum loss reduction in radial distribution system using ABC algorithm. International Journal of Reviews in Computing, 3: 44-52.
[13] Boukaroura, A., Slimani, L., Bouktir, T. (2020). Optimal placement and sizing of multiple renewable distributed generation units considering load variations via dragonfly optimization algorithm. Iranian Journal of Electrical and Electronic Engineering, 16(3): https://doi.org/10.22068/IJEEE.16.3.353 353-362.
[14] Kamarposhti, M.A., Lorenzini, G., Solyman, A.A.A. (2021). Locating and sizing of distributed generation sources and parallel capacitors using multiple objective particle swarm optimization algorithm. Mathematical Modelling of Engineering Problems, 8(1): 10-24. https://doi.org/10.18280/mmep.080102
[15] Mohamed, A.A., Kamel, S., Selim, A., Khurshaid, T., Rhee, S.B. (2021). Developing a hybrid approach based on analytical and metaheuristic optimization algorithms for the optimization of renewable DG allocation considering various types of loads. Sustainability, 13(8): 4447. https://doi.org/10.3390/su13084447
[18] KHASANOV, Mansur, et al. “Optimal planning DG and BES units in distribution system considering uncertainty of power generation and time-varying load.” Turkish Journal of Electrical Engineering & Computer Sciences 29.2 (2021): 773-795.
[19] Abdel-Mawgoud, H., et al. “A strategy for PV and BESS allocation considering uncertainty based on a modified Henry gas solubility optimizer.” Electric Power Systems Research 191 (2021): 106886.
[20] Abdel-Mawgoud, Hussein, et al. “Simultaneous Allocation of Multiple Distributed Generation Units in Distribution Networks Using Chaotic Grasshopper Optimization Algorithm.” 2019 21st International Middle East Power Systems Conference (MEPCON). IEEE, 2019.
[21] Storn, Rainer, and Kenneth Price. “Differential evolution a simple evolution strategy for fast optimization.” Dr. Dobb’s journal 22.4 (1997): 18-24.
[22] MahdiAzizi and al, Energy valley optimizer: a novel metaheuristic algorithm for global and engineering optimization. Springer Nature.
[23] M. E. Baran and F. F. Wu, “Network reconfiguration in distribution systems for loss reduction and load balancing,” IEEE Transactions on Power delivery, vol. 4, no. 2, pp. 1401 1407, 1989.
[24] A. Rana, J. Darji, and M. J. I. J. S. R. D. Pandya, “Backward/forward sweep load flow algorithm for radial distribution system,” vol. 2, no. 1, pp. 398-400, 2014.
[25] Prakash, D.B., Lakshminarayana, C. (2018). Multiple DG placements in radial distribution system for multi objectives using Whale Optimization Algorithm. Alexandria Engineering Journal, 57(4): 2806.https://doi.org/10.1016/j.aej.2017.11.003
[26] 2797 Rama Prabha, D., Jayabarathi, T. (2016). Optimal placement and sizing of multiple distributed generating units in distribution networks by invasive weed optimization algorithm. Ain Shams Engineering Journal, 7(2): 694.https://doi.org/10.1016/j.asej.2015.05.014 683
[27] Mareddy, P.L., Reddy, S., Reddy, V.C.V. (2010). Optimal DG placement for maximum loss reduction in radial distribution system using ABC algorithm. International Journal of Reviews in Computing, 3: 44-52.
[28] Samala, R.K., Kotaputi, M.R. (2017). Multi distributed generation placement using ant-lion optimization. European Journal of Electrical Engineering, https://doi.org/10.3166/EJEE.19.253-267 pp 253-267.
[29] Imene, D., Djemai, N., Ahmed, S., Anes, B. (2021). Optimal DG integration using artificial ecosystem-based optimization (AEO) algorithm. European Journal of Electrical Engineering, Vol. 24, No. 1, pp. 21-26. https://doi.org/10.18280/ejee.240103.

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