Generation Scheduling Under a CO2 Emission Reduction Policy in the Deregulated Market

CO2 emission reduction is important to the sustainable development of the electric power industry. In this paper, we propose a CO2 emission reduction policy for the thermal generation scheduling problem in the deregulated electricity market. By introducing a variable penalty factor, the policy is designed to apply a different penalty mode according to the range of the emissions quantity. The objective of the scheduling is to maximize the generation profits, which are determined by the electricity sales revenue, the generating cost, and the emissions penalty over the planning horizon. Using a piecewise linear function to express the variable penalty factor, the problem is formulated as a mixed integer nonlinear programming model. A variable splitting-based Lagrangian relaxation algorithm is developed to solve the problem. The numerical results for test cases of different sizes show that the proposed algorithm can find near-optimal solutions in a reasonable time. Additionally, the choice of the number of the penalty modes and the effectiveness of the proposed emission reduction policy are discussed.