Effective Incentives Design for Renewable Energy Generation Expansion Planning: An Inverse Optimization Approach

We present an incentive policy design model consisting of lower level and upper level optimization to promote renewable energy. The lower level optimization is a generation expansion planning (GEP) problem, in which the planner aims to expand an energy system's generation capacity to serve projected load with minimum cost. In the upper level optimization, to achieve the goal of specific percentage of renewable energy, the policy maker minimizes the total incentive cost and applies incentive policy to influence the decision of lower level generation planner. We introduce an effective cutting plane algorithm to solve our model. The model is implemented for a simple coal and electricity network. Different effects of mandatory policy model and incentive policy design model are analyzed to provide the optimal policy.