Optimally Designed Subsidies for Achieving Carbon Emissions Targets in Electric Power Systems

One of the major contributors to global warming is the amount of carbon dioxide (CO
₂
) released from burning fossil fuel (primarily coal) as a by-product of the production of electric energy. Imposing carbon taxes to mitigate the emissions from the electricity sector is a well-established method to counteract the detrimental effects of CO
₂
on the environment. This added tax, however, has a negative impact on the economy and wholesale electricity prices. A fact that is more evident when regulating authorities set higher reduction targets which require a higher tax rate. This paper proposes a framework in which regulating authorities can use the revenue from the levied taxes to subsidize more expensive producers that have lower CO
₂
emissions, allowing them to be more competitive in the day-ahead energy market. The problem is formulated as a bilevel optimization in which the upper level represents the regulating authority whose objective function is to minimize the total cost of subsidies given to producers and the lower level represents the day-ahead market clearing process. This nonlinear bilevel model is then transformed into a mixed-integer linear programming problem that can be solved using commercial tools. Numerical studies demonstrate that implementing the proposed approach would make it possible to achieve any feasible emissions target at a much lower tax rate.