SCUC Considering Loads and Wind Power Forecasting Uncertainties using Binary Gray Wolf Optimization Method

  • Majid Moazzami Islamic Azad University, Najafabad Branch.
  • Sayed Jamal al-Din Hosseini Department of Electrical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran.
  • Hossein Shahinzadeh IEEE Member, Department of Electrical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran.
  • Gevork B. Gharehpetian Professor, Department of Electrical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran.
  • Jalal Moradi Young Researchers and Elite Club, Khomeinishahr Branch, Islamic Azad University, Esfahan, Iran
Keywords: Security-constrained unit commitment, Wind power plant, Gray wolf optimization algorithm, Uncertainty, Monte-Carlo.


Recently, the renewable resources such as wind farms assumed more attraction due to their features of being clean, no dependency to any type of fuel and having a low marginal cost. The output power of wind units is dependent on the wind speed which has a volatile and intermittent nature. This fact confronts the solution of unit commitment problem with some challenges when a huge amount of wind resources is penetrated and considerable uncertainties are included in the problem. Moreover, the demand of system has some volatility in comparison with forecasted values. This kind of volatility and stochastic nature is another source of uncertainty in power system. In this paper, thermal and wind units are incorporated and the optimization problem is solved by the employment of proper probability distribution function and Monte Carlo simulation approach for dealing with uncertainties. Afterwards, the optimization problem is solved by the use of the binary form of gray wolf optimization algorithm and the minimized total cost will be obtained. Ultimately, the unit commitment schedule and optimal generation of each unit are determined and the optimization results are compared with the solution of genetic algorithm and particle swarm algorithm.


[1] Shao, Chengcheng, Xifan Wang, Mohammad Shahidehpour, Xiuli Wang, and Biyang Wang. "Security-constrained unit commitment with flexible uncertainty set for variable wind power." IEEE Transactions on Sustainable Energy 8, no. 3 (2017): 1237-1246.
[2] Nikoobakht, Ahmad, Mohammad Mardaneh, Jamshid Aghaei, Victoria Guerrero-Mestre, and Javier Contreras. "Flexible power system operation accommodating uncertain wind power generation using transmission topology control: an improved linearised AC SCUC model." IET Generation, Transmission & Distribution 11, no. 1 (2017): 142-153.
[3] Bavafa, Farhad, Taher Niknam, Rasoul Azizipanah-Abarghooee, and Vladimir Terzija. "A New Biobjective Probabilistic Risk-Based Wind-Thermal Unit Commitment Using Heuristic Techniques." IEEE Transactions on Industrial Informatics 13, no. 1 (2017): 115-124.
[4] Rong, Aiying, and Peter B. Luh. "A Dynamic Regrouping Based Dynamic Programming Approach for Unit Commitment of the Transmission-constrained Multi-site Combined Heat and Power System." IEEE Transactions on Power Systems (2017).
[5] Nemati, Mohsen, Martin Braun, and Stefan Tenbohlen. "Optimization of unit commitment and economic dispatch in microgrids based on genetic algorithm and mixed integer linear programming." Applied Energy (2017).
[6] Najafi, Arsalan, Mohsen Farshad, and Hamid Falaghi. "A new heuristic method to solve unit commitment by using a time-variant acceleration coefficients particle swarm optimization algorithm." Turkish Journal of Electrical Engineering & Computer Sciences23, no. 2 (2015): 354-369.
[7] Canizes, Bruno, João Soares, Pedro Faria, and Zita Vale. "Mixed integer non-linear programming and Artificial Neural Network based approach to ancillary services dispatch in competitive electricity markets." Applied energy 108 (2013): 261-270.
[8] Yu, Xiang, and Xueqing Zhang. "Unit commitment using Lagrangian relaxation and particle swarm optimization." International Journal of Electrical Power & Energy Systems 61 (2014): 510-522.
[9] Barani, Fatemeh, Mina Mirhosseini, Hossein Nezamabadi-pour, and Malihe M. Farsangi. "Unit commitment by an improved binary quantum GSA." Applied Soft Computing 60 (2017): 180-189.
[10] Mirjalili, Seyedali, Shahrzad Saremi, Seyed Mohammad Mirjalili, and Leandro dos S. Coelho. "Multi-objective grey wolf optimizer: a novel algorithm for multi-criterion optimization." Expert Systems with Applications 47 (2016): 106-119.
[11] Sulaiman, Mohd Herwan, Zuriani Mustaffa, Mohd Rusllim Mohamed, and Omar Aliman. "Using the gray wolf optimizer for solving optimal reactive power dispatch problem." Applied Soft Computing 32 (2015): 286-292.
[12] Uçkun, Canan, Audun Botterud, and John R. Birge. "An improved stochastic unit commitment formulation to accommodate wind uncertainty." IEEE Transactions on Power Systems 31, no. 4 (2016): 2507-2517.
[13] Shahinzadeh, Hossein, S. Hamid Fathi, Majid Moazzami, and Seyed Hossein Hosseinian. "Hybrid Big Bang-Big Crunch Algorithm for solving non-convex Economic Load Dispatch problems." In Swarm Intelligence and Evolutionary Computation (CSIEC), 2017 2nd Conference on, pp. 48-53. IEEE, 2017.
[14] Shahinzadeh, Hossein, Majid Moazzami, Davoud Fadaei, and Sepideh Rafiee-Rad. "Glowworm swarm optimization algorithm for solving non-smooth and non-convex economic load dispatch problems." In Fuzzy and Intelligent Systems (CFIS), 2017 5th Iranian Joint Congress on, pp. 103-109. IEEE, 2017.
[15] Wen, Yunfeng, Chuangxin Guo, Hrvoje Pandzic, and Daniel S. Kirschen. "Enhanced security-constrained unit commitment with emerging utility-scale energy storage." IEEE Transactions on Power Systems 31, no. 1 (2016): 652-662.
[16] Shahinzadeh, Hossein, Sayed Mohsen Nasr-Azadani, and Nazereh Jannesari. "Applications of particle swarm optimization algorithm to solving the economic load dispatch of units in power systems with valve-point effects." International Journal of Electrical and Computer Engineering 4, no. 6 (2014): 858.
[17] Xu, Ti, and Ning Zhang. "Coordinated operation of concentrated solar power and wind resources for the provision of energy and reserve services." IEEE Transactions on Power Systems 32, no. 2 (2017): 1260-1271.
[18] Cui, Mingjian, Jie Zhang, Hongyu Wu, Bri-Mathias Hodge, Deping Ke, and Yuanzhang Sun. "Wind power ramping product for increasing power system flexibility." In Transmission and Distribution Conference and Exposition (T&D), 2016 IEEE/PES, pp. 1-5. IEEE, 2016.
[19] Shahinzadeh, Hossein, Alireza Gheiratmand, Jalal Moradi, and S. Hamid Fathi. "Simultaneous operation of near-to-sea and off-shore wind farms with ocean renewable energy storage." In Renewable Energy & Distributed Generation (ICREDG), 2016 Iranian Conference on, pp. 38-44. IEEE, 2016.
[20] Moazzami, Majid, Gevork B. Gharehpetian, Hossein Shahinzadeh, and Seyed Hossein Hosseinian. "Optimal locating and sizing of DG and D-STATCOM using Modified Shuffled Frog Leaping Algorithm." In Swarm Intelligence and Evolutionary Computation (CSIEC), 2017 2nd Conference on, pp. 54-59. IEEE, 2017.
[21] Mirjalili, Seyedali, Seyed Mohammad Mirjalili, and Andrew Lewis. "Grey wolf optimizer." Advances in Engineering Software 69 (2014): 46-61.
[22] Mirjalili, Seyedali. "How effective is the Grey Wolf optimizer in training multi-layer perceptrons." Applied Intelligence 43, no. 1 (2015): 150-161.
[23] Emary, Eid, Hossam M. Zawbaa, and Aboul Ella Hassanien. "Binary grey wolf optimization approaches for feature selection." Neurocomputing 172 (2016): 371-381.
[24] Graf, Peter A., Gordon Stewart, Matthew Lackner, Katherine Dykes, and Paul Veers. "High‐throughput computation and the applicability of Monte Carlo integration in fatigue load estimation of floating offshore wind turbines." Wind Energy 19, no. 5 (2016): 861-872.
[25] Moazzami, Majid, Sayed Jamal al-Din Hosseini, and Hossein Shahinzadeh. "Optimal Sizing of an Isolated Hybrid Wind/PV/Battery System with Considering Loss of Power Supply Probability." Majlesi Journal of Electrical Engineering 11, no. 3 (2017).
[26] Shahinzadeh, Hossein, Alireza Gheiratmand, S. Hamid Fathi, and Jalal Moradi. "Optimal design and management of isolated hybrid renewable energy system (WT/PV/ORES)." In Electrical Power Distribution Networks Conference (EPDC), 2016 21st Conference on, pp. 208-215. IEEE, 2016.
[27] Shahinzadeh, Hossein, Majid Moazzami, S. Hamid Fathi, and Gevork B. Gharehpetian. "Optimal sizing and energy management of a grid-connected microgrid using HOMER software." In Smart Grids Conference (SGC), 2016, pp. 1-6. IEEE, 2016.
[28] Kavousi-Fard, Abdollah, and Taher Niknam. "Multi-objective probabilistic distribution feeder reconfiguration considering wind power plants." International Journal of Electrical Power & Energy Systems 55 (2014): 680-691.
[29] Mohseni-Bonab, S. M., A. Rabiee, S. Jalilzadeh, B. Mohammadi-Ivatloo, and S. Nojavan. "Probabilistic multi objective optimal reactive power dispatch considering load uncertainties using Monte Carlo simulations." Journal of Operation and Automation in Power Engineering 3, no. 1 (2015): 83-93.
[30] Daneshi, Ali, Nima Sadrmomtazi, Mojtaba Khederzadeh, and Javad Olamaei. "Integration of wind power and energy storage in SCUC problem." In World Non-Grid-Connected Wind Power and Energy Conference (WNWEC), 2010, pp. 1-8. IEEE, 2010.
[31] Shahidehpour, Mohammad, Hatim Yamin, and Zuyi Li. "Market overview in electric power systems." Market Operations in Electric Power Systems: Forecasting, Scheduling, and Risk Management(2002): 1-20.
How to Cite
Moazzami, M., Hosseini, S. J. al-D., Shahinzadeh, H., Gharehpetian, G. B., & Moradi, J. (2018). SCUC Considering Loads and Wind Power Forecasting Uncertainties using Binary Gray Wolf Optimization Method. Majlesi Journal of Electrical Engineering, 12(4), 15-24. Retrieved from