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

Majlesi Journal of Electrical Engineering

مقاله 5، دوره 12، شماره 4، اسفند 2018، صفحه 15-24   

نوع مقاله: Review Article

نویسندگان

Majid Moazzami^{* 1}؛ Sayed Jamal al-Din Hosseini²؛ Hossein Shahinzadeh³؛ Gevork B. Gharehpetian⁴؛ Jalal Moradi⁵

¹Islamic Azad University, Najafabad Branch.

²Department of Electrical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran.

³IEEE Member, Department of Electrical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran.

⁴Professor, Department of Electrical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran.

⁵Young Researchers and Elite Club, Khomeinishahr Branch, Islamic Azad University, Esfahan, Iran

چکیده

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.

کلیدواژه‌ها

Security-constrained unit commitment؛ Wind power plant؛ Gray Wolf Optimization Algorithm؛ Uncertainty؛ Monte-Carlo

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