This paper reviews the different aspects of modeling wind energy systems namely investment, policies, performance, and social benefits for integration in deregulated power market. The wind energy system models depend on wind resource, electrical response of wind turbine generator and the returns of economic market. The paper focuses on identifying the sub-problems and their modeling approaches. Variability of the local power system and the wind resource are chaotic and are usually difficult to model. Satisfactory and some successful algorithms are discussed in detail. Machine Learning models are presented to predict market return and described by market trend and resource forecast. This paper, proposes the representation of risk from large wind integration in unit commitment and presents regional aggregation. The review is followed by critical costs modeling for wind energy projects and market risk mitigation strategies. Finally, social impact and energy security compliance from large scale wind integration are reviewed.