China’s Energy Portfolio Optimization Study Based on Multi-Attribute Utility Theory and Genetic Algorithm Method

Abstract

China’s energy planning problem was concluded to the energy portfolio optimization problem which was solved by multi-attribute utility theory and genetic algorithm methods. A fundamental objectives hierarchy was established to structure the energy technology alternatives. Based on this hierarchy model, weights and utilities of energy resources were calculated by the multi-attribute utility theory. The Evolver decision tool was used to find an optimal energy portfolio by the genetic algorithm. The results indicated China should reduce coal and nuclear power in the future energy portfolio.