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The Vector Optimization Method for Solving Integer Linear Programming Problems: Application for the Unit Commitment Problem in Electrical Power Production

In: Large Scale Optimization in Supply Chains and Smart Manufacturing

Author

Listed:
  • Lenar Nizamov

    (Kazan State Power Engineering University)

Abstract

Nowadays information technology is continuously implemented in all fields of industry, including power generation. One of the most important tasks of modern energy systems is reliable, effective, and safe planning of their work. The task of planning is also vital for single power plants. The solution of this task must satisfy requirements of financial effectiveness and conditions of energy system. This chapter deals with the solution of the problem of integer linear programming. For this purpose the author consistently represents the statement of the problem, the objective function, and the system of constraints that must be considered. To solve considered problem, the vector optimization method (VOM) is proposed. To illustrate the performance of the proposed method, the author provided the example of how to solve the unit commitment problem for the power station, in order to reach a maximum total financial profit. As a result of planning, the desired optimal sequence of combinations of operating turbogenerators is determined. To assess effectiveness of the VOM, the chapter provides an estimate of its computational cost in comparison with the computational cost of the dynamic programming method. The comparison results demonstrate the advantages of the VOM.

Suggested Citation

  • Lenar Nizamov, 2019. "The Vector Optimization Method for Solving Integer Linear Programming Problems: Application for the Unit Commitment Problem in Electrical Power Production," Springer Optimization and Its Applications, in: Jesús M. Velásquez-Bermúdez & Marzieh Khakifirooz & Mahdi Fathi (ed.), Large Scale Optimization in Supply Chains and Smart Manufacturing, pages 241-256, Springer.
    • Handle: RePEc:spr:spochp:978-3-030-22788-3_8
    DOI: 10.1007/978-3-030-22788-3_8
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