Abstract
Due to economic development and the improvement of people’s living standards, questions that the imbalance of energy supply and demand as well as the environmental damage have become increasingly prominent. To study the contradiction between energy and environment, and considering there are a lot of uncertain factors in the actual planning, this paper improves a chance-constrained interval type-2 fuzzy method used in linear programming and extends the interval type-2 fuzzy number to the general type-2 fuzzy number by introducing the secondary membership function that makes up for the loss of uncertainty due to the fixed value of the second membership function and optimizes the accuracy of the probability in the original method. By applying the new method to the energy planning system model, an optimal planning plan with the goal of reducing air pollutant emissions as well as the lowest overall operating cost can be obtained. Compared with the interval fuzzy method, the new method proposed in this paper is able to deal with the uncertainty in the system better, and provides more accurate solutions under different satisfaction levels.
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