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• W3217314272 abstract "This paper proposes an optimization method for energy planning that will efficiently meet multiple requirements subject to uncertain future projections. A stochastic optimization model is used to identify appropriate energy mixes under various scenarios of uncertainty, and the performance of three different energy policies—a pro-economic policy, a pro-environmental policy, and a governmental plan—is compared. Data envelopment analysis is applied to measure the relative energy efficiency of the optimized energy mixes in providing energy security, energy equity, and environmental sustainability. Thailand’s power development plan for 2032 is used as a case study to illustrate the approach. Analysis of the case study indicates that the pro-environmental policy is the most efficient of the three policies considered. Empirical results from this study provide quantitative support for policy makers seeking to establish an efficient energy policy to satisfy the three requirements while allowing for a range of future uncertainties." @default.
• W3217314272 created "2021-12-06" @default.
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• W3217314272 date "2022-04-01" @default.
• W3217314272 modified "2023-09-25" @default.
• W3217314272 title "Measuring the efficiency of energy planning under uncertainty" @default.
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• W3217314272 doi "https://doi.org/10.1016/j.egyr.2021.11.164" @default.
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