Unit commitment in smart grids with wind farms using virus colony search algorithm and considering adopted bidding strategy

The significant ongoing technical and scientific advancements in renewable generation technologies and developments in smart grids' infrastructures have reduced their prices and costs to an affordable economical level. Hence, in the last decade, integration of renewable energies has had conspicuous pervasiveness, and the structures of power networks have been evolving to smart grid styles. The intelligently operated grids and more penetration of green energies facilitate alleviation of the generation expenditures, mitigation of greenhouse gases emissions, and achieving more efficient exploitation of installed generation resources. Aside from various uncertainties in power system operation, the inclusion of renewable resources, which are mainly intermittent in nature, encounters the power system operation scheduling with severe challenges. Therefore, the uncertainties of renewable resources such as wind and solar energy resources, as well as inherent uncertainties of power systems such as load forecast inaccuracies must be included mathematically in the operation schedules. The consideration of such uncertainties improves the robustness against plausible volatilities and contingencies and provides a more secure operation. The incorporation of various uncertainties into the unit commitment program deteriorates the solution of the problem in term of complexity. The solution of such a sophisticated problem which comprises time-oriented and practical constraints requires either appropriate exact or heuristic approaches. In this paper, a 10-generator test system is selected for simulations, and the virus colony search (VCS) algorithm is employed to solve unit commitment problem considering the impact of the presence of intermittent wind farms. Ultimately, the economic dispatch is performed between committed units, and operational costs are also calculated. The uncertainties of wind and load forecasts are incorporated in the system modeling through three scenarios. These scenarios demonstrate the impact of the presence of wind units in smart grids, and the way uncertainties affect the electricity network operation economically. Besides, the way wind farms must treat with such uncertainties through appropriate bidding strategy is investigated in order to protect themselves from high prices of spot market and plausible detriments.