Using integer programming to refine Lagrangian-based unit commitment solutions

Takriti, Samer; Birge, John R.

doi:10.1109/59.852114

Cited by 98 publications

(67 citation statements)

References 18 publications

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“…The minimum up/downtime restrictions ensure that the on/off status of the generators do not change rapidly. Frequent state transitions have several adverse consequences including (i) increased operator stress, (ii) diminished generator life, and (iii) increased emission of pollutants during transient periods (see [25]). Such restrictions are quite practical and are included in many commercial tools.…”

Section: A Formulating the Componentsmentioning

confidence: 99%

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A State Transition MIP Formulation for the Unit Commitment Problem

Atakan

Lulli

Sen

2018

IEEE Trans. Power Syst.

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Abstract-In this paper, we present the state-transition formulation for the unit commitment (UC) problem. This formulation uses new decision variables that capture the state transitions of the generators, instead of their on/off statuses. We show that this new approach produces a formulation which naturally includes valid inequalities, commonly used to strengthen other formulations. We demonstrate the performance of the statetransition formulation and observe that it leads to improved solution times especially in longer time-horizon instances. As an important consequence, the new formulation allows us to solve realistic instances in less than 12 minutes on an ordinary desktop PC, leading to a speed-up of a factor of almost two, in comparison to the nearest contender. Finally, we demonstrate the value of considering longer planning horizons in UC problems.

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Section: A Formulating the Componentsmentioning

confidence: 99%

“…Such restrictions are quite practical and are included in many commercial tools. To formulate these restrictions, several constraints were proposed in [24], [25], [26]. Following [11], the minimum uptime and downtime constraints are best formulated using the following constraints:…”

Section: A Formulating the Componentsmentioning

confidence: 99%

A State Transition MIP Formulation for the Unit Commitment Problem

Atakan

Lulli

Sen

2018

IEEE Trans. Power Syst.

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“…To overcome this issue, in [22] integer programming techniques are developed for refining the UC solution obtained from solving the dual problem, by using the schedules generated by the different iterations of the Lagrangian method.…”

Section: Lagrangian Heuristics For the Uc Of Thermal Unitsmentioning

confidence: 99%

Lagrangian heuristics based on disaggregated bundle methods for hydrothermal unit commitment

Borghetti

Frangioni

Lacalandra

et al. 2003

IEEE Trans. Power Syst.

128

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Abstract-The paper presents a simple and effective Lagrangian relaxation approach for the solution of the optimal short-term unit commitment problem in hydrothermal power-generation systems. The proposed approach, based on a disaggregated Bundle method for the solution of the dual problem, with a new warm-starting procedure, achieves accurate solutions in few iterations. The adoption of a disaggregated Bundle method not only improves the convergence of the proposed approach but also provides information that are suitably exploited for generating a feasible solution of the primal problem and for obtaining an optimal hydro scheduling. A comparison between the proposed Lagrangian approach and other ones, based on sub-gradient and Bundle methods, is presented for a simple yet reasonable formulation of the Hydrothermal Unit Commitment problem.

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“…Spurred by the progress in the technology of processors and computers, many authors used the MIP formulation for the UC problem for on-land power systems (see e.g. [1], [6], [10], and [4]). In such formulations, a binary variable is used to indicate the status of each generator.…”

Section: Ut Jmentioning

confidence: 99%

“…3) Power generation: The power generated by each generator is bounded from above and below according to manufacturer recommendations, that is, P j ≤ p j (t) ≤ P j , ∀ j ∈ J , ∀t ∈ T . The binary variable u(t) is, usually, included in this inequality, that is to say ( [1], [4], and [6]):…”

Section: A Assumptions and Constraintsmentioning

confidence: 99%

Mixed-integer formulation of unit commitment problem for power systems: Focus on start-up cost

Tuffaha

Gravdahl

2013

IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society

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Abstract-In this work, the Mixed-Integer (MIP) formulation for unit commitment problem (UC) for power systems is discussed. A new formulation for the start-up cost is suggested as well. This new formulation of the start-up cost exploits the transformation of the conditional statements into inequalities that comprise linear combination of binary variables. Solutions of the suggested optimization problem were obtained. A comparison between these solutions and those of a strategy common in literature is held to show that the new strategy gives same results with less number of constraints and tighter capture of the startup cost.

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Using integer programming to refine Lagrangian-based unit commitment solutions

Cited by 98 publications

References 18 publications

A State Transition MIP Formulation for the Unit Commitment Problem

A State Transition MIP Formulation for the Unit Commitment Problem

Lagrangian heuristics based on disaggregated bundle methods for hydrothermal unit commitment

Mixed-integer formulation of unit commitment problem for power systems: Focus on start-up cost

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