The demand for energy is constantly rising in the world while most of the conventional sources of energy are getting more scarce and expensive. Additionally, environmental issues such as dealing with excessive greenhouse gas emissions (especially CO2) impose further constraints on energy industry all over the globe. Therefore, there is an increasing need for the energy sector to raise the share of clean and renewable sources of energy in power generation. Wind power has specifically attracted large scale investment in recent years since it is ample, widely distributed and has minimal environmental impact. Wind flow and consequently wind-generated power have a stochastic nature. Therefore, wind power should be used in combination with more reliable and fuel-based power generation methods. As a result, it is important to investigate how much capacity from each source of energy should be installed in order to meet electricity demand at the desired reliability level while considering cost and environmental implications. For this purpose, a probabilistic optimization model is proposed where demand and wind power generation are both assumed stochastic.The stochastic model uses a combination of recourse and chance-constrained approaches and is capable of assigning optimal production levels for different sources of energy while considering the possibility of importation, exportation and storage of electricity in the network.
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