It should be noted that MILP-based approach is becoming a
mainstream method for solving SCUC problems based on commercial
MILP solvers [8], [17]–[19]. However, the LR-based
approaches are still useful in many cases. This is because to
apply MILP-based methods efficiently, one of the most important
issues is to convert the problem objective and constraints
into a good linear formulation. Therefore, many ancillary variables
and constraints must be introduced to handle minimum
up/down time constraints, variable start-up costs, nonlinear fuel
costs, etc. In some cases, the computation efficiency would be
a serious issue. The approximation error is another important
issue seldom discussed. On the other hand, one can use a more
natural and concise formulation for the LR-based methods and
mainstream method for solving SCUC problems based on commercial
MILP solvers [8], [17]–[19]. However, the LR-based
approaches are still useful in many cases. This is because to
apply MILP-based methods efficiently, one of the most important
issues is to convert the problem objective and constraints
into a good linear formulation. Therefore, many ancillary variables
and constraints must be introduced to handle minimum
up/down time constraints, variable start-up costs, nonlinear fuel
costs, etc. In some cases, the computation efficiency would be
a serious issue. The approximation error is another important
issue seldom discussed. On the other hand, one can use a more
natural and concise formulation for the LR-based methods and
cares less on the problem formation.
引自:A Systematic Method for Constructing Feasible Solution to SCUC Problem With Analytical Feasibility Conditions
Hongyu Wu, Xiaohong Guan, Fellow, IEEE, Qiaozhu Zhai, Member, IEEE, and Hongxing Ye
本文探讨了使用混合整数线性规划(MILP)解决安全约束 Unit Commitment (UC) 问题所存在的不足。研究指出,MILP方法可能对问题的构建不够关注,特别是在确保解的可行性方面。
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