An investigation on the impacts of regulatory interventions on wind power expansion in generation planning

Large integration of intermittent wind generation in power system has necessitated the inclusion of more innovative and sophisticated approaches in power system investment planning. This paper presents a novel framework on the basis of a combination of stochastic dynamic programming (SDP) algorithm and game theory to study the impacts of different regulatory interventions to promote wind power investment in generation expansion planning. In this study, regulatory policies include Feed-in-Tariff (FIT) incentive, quota and tradable green certificate. The intermittent nature and uncertainties of wind power generation will cause the investors encounter risk in their investment decisions. To overcome this problem, a novel model has been derived to study the regulatory impacts on wind generation expansion planning. In our approach, the probabilistic nature of wind generation is modeled. The model can calculate optimal investment strategies, in which the wind power uncertainty is included. This framework is implemented on a test system to illustrate the working of the proposed approach. The result shows that FITs are the most effective policy to encourage the rapid and sustained deployment of wind power. FITs can significantly reduce the risks of investing in renewable energy technologies and thus create conditions conducive to rapid market growth.