Optimal Power Flow considering intermittent Wind Power using Particle Swarm optimization

shilaja chandrasekaran, Ravi K

Abstract


Inclusion of renewable generation in the existing network is necessary due to the increase in raw material cost for generating electricity and growing demand. Optimal power flow incorporating wind generation is solved using Particle swarm optimization (PSO) in this paper. Weibull distribution function is used for modelling the intermittent nature of wind farm and then it is incorporated in the existing power system network. A direct cost function of the wind power purchased is presented in the paper. Cases without and with wind power are solved using PSO due to its ability in solving the non linear problems. The analysis is carried out on IEEE 30 bus test system and the obtained results are compared with the few existing methods. From the results it can be inferred that this method provides enhanced results.

Keywords


Optimal power flow; Wind; PSO; weibull distribution

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References


Mohseni-Bonab, SeyedMasoud, Abbas Rabiee, and Behnam Mohammadi-Ivatloo. "Voltage stability constrained multi-objective optimal reactive power dispatch under load and wind power uncertainties: A stochastic approach."Renewable Energy 85 (2016): 598-609.

Lubin, Miles, YuryDvorkin, and Scott Backhaus. "A Robust Approach to Chance Constrained Optimal Power Flow with Renewable Generation." (2015).

Pandya, Sundaram, and Ranjit Roy. "Particle Swarm Optimization Based Optimal Reactive Power Dispatch." Electrical, Computer and Communication Technologies (ICECCT), 2015 IEEE International Conference on. IEEE, 2015.

Singh, RudraPratap, V. Mukherjee, and S. P. Ghoshal. "Optimal reactive power dispatch by particle swarm optimization with an aging leader and challengers." Applied Soft Computing 29 (2015): 298-309.

Surinkaew, Tossaporn, and IssarachaiNgamroo. "Wide area robust centralized power oscillation dampers design for DFIG-based wind turbines."Power Systems Computation Conference (PSCC), 2014. IEEE, 2014.

Plathottam, S. J., Prakash Ranganathan, and H. Salehfar. "Unbiased optimal power flow for power systems with wind power generation." Electronics Letters 50.18 (2014): 1312.

Le, Dinh Luong, DacLoc Ho, and Ngoc Dieu Vo. "Improved Particle Swarm Optimization Method for Optimal Power Flow with Facts Devices." GMSARN INTERNATIONAL JOURNAL (2015): 37.

Bukhsh, Waqquas Ahmed, et al. "Local solutions of the optimal power flow problem." Power Systems, IEEE Transactions on 28.4 (2013): 4780-4788.

Samorani, Michele. "The wind farm layout optimization problem." Handbook of Wind Power Systems. Springer Berlin Heidelberg, 2013. 21-38.

Haghi, H. Valizadeh, S. M. Hakimi, and SM MoghaddasTafreshi. "Optimal sizing of a hybrid power system considering wind power uncertainty using PSO-embedded stochastic simulation." Probabilistic Methods Applied to Power Systems (PMAPS), 2010 IEEE 11th International Conference on. IEEE, 2010.

Eberhart, Russ C., and James Kennedy. "A new optimizer using particle swarm theory." Proceedings of the sixth international symposium on micro machine and human science. Vol. 1. 1995.

Park, Jong-Bae, et al. "A particle swarm optimization for economic dispatch with nonsmooth cost functions." Power Systems, IEEE Transactions on 20.1 (2005): 34-42.

Ramesh, V., et al. "A novel selective particle swarm optimization approach for combined heat and power economic dispatch." Electric Power Components and Systems 37.11 (2009): 1231-1240.

Shi, Libao, Chen Wang, Liangzhong Yao, Yixin Ni, and Masoud Bazargan. "Optimal power flow solution incorporating wind power." Systems Journal, IEEE 6, no. 2 (2012): 233-241.

Paranjothi, S. R., and K. Anburaja. "Optimal power flow using refined genetic algorithm." Electric Power Components and Systems 30, no. 10 (2002): 1055-1063.

Saini, Ashish, Devendra K. Chaturvedi, and A. K. Saxena. "Optimal power flow solution: a GA-fuzzy system approach." International journal of emerging electric power systems 5, no. 2 (2006).

Abido, M. A. "Optimal power flow using tabu search algorithm." Electric Power Components and Systems 30, no. 5 (2002): 469-483.

Sayah, Samir, and Khaled Zehar. "Modified differential evolution algorithm for optimal power flow with non-smooth cost functions." Energy conversion and Management 49, no. 11 (2008): 3036-3042.

Kumar, A. Ramesh, and L. Premalatha. "Optimal power flow for a deregulated power system using adaptive real coded biogeography-based optimization." International Journal of Electrical Power & Energy Systems 73 (2015): 393-399.




DOI (PDF): https://doi.org/10.20508/ijrer.v6i2.3618.g6811

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