Solution for short-term hydrothermal scheduling with a logarithmic size mixed-integer linear programming formulation

Jinbao Jian, Shanshan Pan and Linfeng Yang

Energy, 2019, vol. 171, issue C, 770-784

Abstract: Short-term hydrothermal scheduling issue is usually hard to tackle on account of its highly non-convex and non-differentiable characteristics. A popular strategy for handling these difficulties is to reformulate the issue by various linearization techniques. However, in this process, a fairly large number of continuous/binary variables and constraints will be introduced, which may result in a heavy computational burden. In this study, a logarithmic size mixed-integer linear programming formulation is presented for this issue, that is, only a logarithmic size of binary variables and constraints will be required to piecewise linearize the nonlinear functions. Based on such a formulation, a global optimum is therefore can be solved efficiently. To remove the linearization errors and cope with the network loss, a derivable non-linear programming formulation is derived. By optimizing this formulation via the powerful interior point method, where the previous global solution of mixed-integer linear programming formulation is used as the starting point, a promising feasible solution is consequently attained. Numerical results show that the presented logarithmic size mixed-integer linear programming formulation is more efficient than the generalized one and when it is incorporated into the solution procedure, the proposed methodology is competitive with currently state-of-the-art approaches.

Keywords: Short-term hydrothermal scheduling; Piecewise linearize; Logarithmic size; Mixed-integer linear programming; Non-linear programming (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:171:y:2019:i:c:p:770-784

DOI: 10.1016/j.energy.2019.01.038

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