Concerns about climate changes and efforts for enhancing supply security have led to an increase in renewable energy resources penetration in power systems. Renewable generations reduce the available flexibility by displacing existing flexible units and simultaneously enhance the need for additional flexibility due to their stochastic nature. In this light, the system is faced with a flexibility gap which must be covered using appropriate ways. This thesis proposes two distinct solutions to provide the required system flexibility in the presence of wind power generation. The first solution is pertained to coordinated scheduling of supply-side and emerging flexible resources such as demand response, bulk energy storages, and plug-in electric vehicle parking lots. The mentioned resources have been modeled considering their own specific constraints and then, the energy and reserve markets clearing procedure has been formulated through a two-stage stochastic programming approach. Afterward, different combinations of flexible resources are defined as separate case studies and their mutual impacts have been analyzed. Finally, various generation mixtures are prioritized applying multi criteria decision making technique based on the system operator’s economic, technical, and environmental desires to provide a guideline to opt the most effective generation mixture in the context of flexibility promotion. The second solution is associated with modeling and investigating the ramp product alongside energy and reserve markets. To this end, a near to practice model has been presented and the effect of ramp product consideration on generation scheduling has been investigated. In addition, the impact of incorporation of flexible resources on the ramp market transactions has been evaluated. In order to compare the flexibility of different generation units, an innovative techno-economic flexibility measure has been developed. Afterward, day-ahead generation scheduling has been performed using the proposed flexibility index through a bi-objective model including operation cost as well as generation dispatch flexibility. Moreover, the impacts of employing each of emerging flexible resources on the generation scheduling and Pareto front has been evaluated.