Bilevel Flexible-Robust Optimization for Energy Allocation Problems

被引:6
作者
Biswas, Arpan [1 ]
Chen, Yong [2 ]
Gibson, Nathan [3 ]
Hoyle, Christopher [1 ]
机构
[1] Oregon State Univ, Dept Mech Engn, Corvallis, OR 97331 USA
[2] Oregon State Univ, Coll Agr Sci, Corvallis, OR 97331 USA
[3] Oregon State Univ, Dept Math, Corvallis, OR 97331 USA
来源
ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING | 2020年 / 6卷 / 03期
关键词
bilevel optimization; flexible-robust optimization; real option analysis; KL-expansion; stochastic collocation; DIMENSION REDUCTION; DESIGN; MODEL; FLEXIBILITY; VALUATION; SYSTEM;
D O I
10.1115/1.4046269
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
A common issue in energy allocation problems is managing the tradeoff between selling surplus energy to maximize short-term revenue, versus holding surplus energy to hedge against future shortfalls. For energy allocation problems, this surplus represents resource flexibility. The decision maker has an option to sell or hold the flexibility for future use. As a decision in the current period can affect future decisions significantly, future risk evaluation of uncertainties is recommended for the current decision in which a traditional robust optimization is not efficient. Therefore, an approach to flexible-robust optimization has been formulated by integrating a real options (RO) model with the robust optimization framework. In the energy problem, the real option model evaluates the future risk, and provides the value of holding flexibility, whereas the robust optimization quantifies uncertainty and provides a robust solution of net revenue by selling flexibility. This problem is solved using bilevel programming and a complete general mathematical formulation of bilevel flexible-robust optimization model is presented for multireservoir systems and results shown to provide an efficient decision making process in energy sectors. To reduce the computational expense, mathematical techniques have been used in the proposed model to reduce the dimension in the quantification and propagation of uncertainties.
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页数:15
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