A Method for Optimal Power System Expansion Planning under Uncertain CO₂ Emissions Control Policies

Abstract

Many efforts towards a settlement of the CO₂ problem have already been made through internationally organized meetings. It is not unlikely that some targets will be set for the reduction of CO₂ emissions. If a stringent reduction target should be imposed on CO₂ emitted from a national energy system, this can possibly have as severe an impact upon electric power sectors as the oil price crises experienced in the seventies. It is, however, quite uncertain whether or not political muscles will be used specifically for tackling the CO₂ problem in the near future.
In such a context, this paper presents a new method for optimal power system planning under uncertain CO₂ emissions control policies. The derived optimal expansion plan gives us the minimum expected value of the sum of the total system cost and the total amount of carbon taxes levied on net CO₂ emissions from fossil fuel-fired power plants. The stochastic dynamic optimization problem discussed here is formulated as a linear programming problem decomposable into several small sub-problems. The proposed method can take into account a specific future scenario of the magnitude of control policy uncertainties, which can be presumably resolved in the first half of the next century due to the increase in scientific wisdom.
In order to evaluate the usefulness of the method proposed here, the authors also present a simple case study with the Japanese national power system up to the year of 2050.