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Optimal power system expansion planning under uncertain CO 2 emissions control policies
Author(s) -
Fujii Yasumasa,
Akimoto Keigo
Publication year - 1996
Publication title -
electrical engineering in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.136
H-Index - 28
eISSN - 1520-6416
pISSN - 0424-7760
DOI - 10.1002/eej.4391170501
Subject(s) - context (archaeology) , dynamic programming , optimal control , electric power system , mathematical optimization , control (management) , stochastic programming , fossil fuel , power (physics) , reduction (mathematics) , settlement (finance) , operations research , order (exchange) , plan (archaeology) , computer science , economics , engineering , mathematics , waste management , finance , history , physics , archaeology , quantum mechanics , payment , biology , artificial intelligence , paleontology , geometry
Many efforts towards a settlement of the CO 2 problem have already been made through internationally organized meetings. It is not unlikely that some targets will be set for the reduction of CO 2 emissions. If a stringent reduction target should be imposed on CO 2 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 CO 2 problem in the near future. In such a context, this paper presents a new method for optimal power system planning under uncertain CO 2 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 CO 2 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 subproblems. 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 2050.