Deterministic and probabilistic multi-objective placement and sizing of wind renewable energy sources using improved spotted hyena optimizer. (1st March 2021)

• Record Type: Journal Article
• Authors: Naderipour, Amirreza; Nowdeh, Saber Arabi; Saftjani, Parvin Barat; Abdul-Malek, Zulkurnain; Bin Mustafa, Mohd Wazir; Kamyab, Hesam; Davoudkhani, Iraj Faraji
• Is Part Of: Journal of cleaner production. Volume 286(2021)
• Publication Date: 2021-03-01
• Subjects: Distribution network -- Wind turbine -- Deterministic and probabilistic placement and sizing -- Uncertainty -- Monte Carlo simulation -- β-Chaotic sequence spotted hyena optimizer; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2020.124941
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: In this paper, deterministic and probabilistic optimal placement and sizing of wind turbines (WTs) in distribution networks are investigated with two objectives: reducing loss and improving voltage profile and stability index. A new improved meta-heuristic method, named β -chaotic sequence spotted hyena optimizer, is proposed to determine the optimal size and location of wind turbines. The proposed method is implemented on IEEE 33-bus and 69-bus radial distribution networks. The performance of the method is verified with finding the optimal location and size of WTs, which exhibited lower power loss and better minimum voltage and voltage stability index with more convergence speed in comparison with the conventional spotted hyena optimizer and particle swarm optimization, and previous studies. Additionally, the probabilistic placement and sizing of WTs are implemented considering the uncertainty of wind generation and the network demand based on Monte Carlo simulation. The results showed that losses increased, the voltage profile weakened, and the voltage stability index was reduced, compared with the deterministic method. For 33 bus network, the loss, minimum voltage, and voltage stability index in two WTs application are recorded as 28.79 kW, 0.9811, and 31.12 p. u, respectively, using the deterministic method, while the values of 34.56 kW, 0.9789, and 30.72 p. u are recorded using the probabilistic method. On the other hand, for 69 bus network, these values are recorded as 18.60 kW, 0.9833, and 67.13 p. u using the deterministic method, and 29.36 kW, 0.9794, and 65.62 p. u using the probabilistic method. Therefore, the resultsclearly show that the probabilistic method is more realistic and accurate than the deterministic method due to consideration of load and wind generation intrinsic changes with all possible probabilities, based on which the network operators can have a more accurate view of the impact of renewable resources on the network characteristics, hence making better decisions to improve them. Highlights: Deterministic and probabilistic optimal placement and sizing of wind turbines. A new improved meta-heuristic method, named β -chaotic sequence spotted hyena optimizer. Due to the consideration of the load, the proposed method is more realistic and accurate. Better minimum voltage and voltage stability index with more convergence speed.